Management of sharps in ambulance care : a state-wide survey of paramedic knowledge and reported practice

Paramedics are at high risk of exposure to infectious diseases because they frequently undertake procedures such as the use and disposal of sharps as components of everyday practice. While the literature demonstrates that the management of sharps is problematic across all health disciplines, there is a paucity of research examining sharps management practices in the Australian pre-hospital paramedic context. This study examines knowledge and practices of sharps control among paramedics in Queensland, Australia. A mail survey focusing on infection control knowledge and practices was sent to all clinical personnel of the Queensland Ambulance Service (QAS) (N = 2274). A total of 1258 surveys were returned, a response rate of 55.3%. Participants responded to 12 true/false statements on the management of sharps and three questions about recapping practices. Most respondents were knowledgeable about the correct management of sharps, with a mean of 11.28 (out of 12, SD = 1.32). When gauging reported practices, more than half (59.1%, n = 736) of participants reported recapping a needle, and 38.5% (n = 479) reported never having done so. These results reflect good knowledge of general management of sharps among respondents, but suggest deficits regarding reported practices. The results suggest that a comprehensive ambulance in-service education programme focusing particularly on sharps management is required. The study highlights the need for further research on sharps management practices in the field, identification of barriers to safe sharps practices in pre-hospital settings, and 'best practice' for translating good sharps management knowledge into practice.

PhD forum : multiple camera management using wide base-line matching

Manual calibration of large and dynamic networks of cameras is labour intensive and time consuming. This is a strong motivator for the development of automatic calibration methods. Automatic calibration relies on the ability to find correspondences between multiple views of the same scene. If the cameras are sparsely placed, this can be a very difficult task. This PhD project focuses on the further development of uncalibrated wide baseline matching techniques.

Bringing academics on board : encouraging institution-wide diffusion of e-learning environments

Rapid advances in educational and information communications technology (ICT)have encouraged some educators to move beyond traditional face to face and distance education correspondence modes toward a rich, technology mediated e-learning environment. Ready access to multimedia at the desktop has provided the opportunity for educators to develop flexible, engaging and interactive learning resources incorporating multimedia and hypermedia. However, despite this opportunity, the adoption and integration of educational technologies by academics across the tertiary sector has typically been slow. This paper presents the findings of a qualitative study that investigated factors influencing the manner in which academics adopt and integrate educational technology and ICT. The research was conducted at a regional Australian university, the University of Southern Queensland (USQ), and focused on the development of e-learning environments. These e-learning environments include a range of multimodal learning objects and multiple representations of content that seek to cater for different learning styles and modal preferences, increase interaction, improve learning outcomes, provide a more inclusive and equitable curriculum and more closely mirror the on campus learning experience. This focus of this paper is primarily on the barriers or inhibitors academics reported in the study, including institutional barriers, individual inhibitors and pedagogical concerns. Strategies for addressing these obstacles are presented and implications and recommendations for educational institutions are discussed.

Wide-angle visual feature matching for outdoor localization

Wide-angle images exhibit significant distortion for which existing scale-space detectors such as the scale-invariant feature transform (SIFT) are inappropriate. The required scale-space images for feature detection are correctly obtained through the convolution of the image, mapped to the sphere, with the spherical Gaussian. A new visual key-point detector, based on this principle, is developed and several computational approaches to the convolution are investigated in both the spatial and frequency domain. In particular, a close approximation is developed that has comparable computation time to conventional SIFT but with improved matching performance. Results are presented for monocular wide-angle outdoor image sequences obtained using fisheye and equiangular catadioptric cameras. We evaluate the overall matching performance (recall versus 1-precision) of these methods compared to conventional SIFT. We also demonstrate the use of the technique for variable frame-rate visual odometry and its application to place recognition.

Wide-baseline keypoint detection and matching with wide-angle images for vision based localisation

This thesis addresses the problem of detecting and describing the same scene points in different wide-angle images taken by the same camera at different viewpoints. This is a core competency of many vision-based localisation tasks including visual odometry and visual place recognition. Wide-angle cameras have a large field of view that can exceed a full hemisphere, and the images they produce contain severe radial distortion. When compared to traditional narrow field of view perspective cameras, more accurate estimates of camera egomotion can be found using the images obtained with wide-angle cameras. The ability to accurately estimate camera egomotion is a fundamental primitive of visual odometry, and this is one of the reasons for the increased popularity in the use of wide-angle cameras for this task. Their large field of view also enables them to capture images of the same regions in a scene taken at very different viewpoints, and this makes them suited for visual place recognition. However, the ability to estimate the camera egomotion and recognise the same scene in two different images is dependent on the ability to reliably detect and describe the same scene points, or ‘keypoints’, in the images. Most algorithms used for this purpose are designed almost exclusively for perspective images. Applying algorithms designed for perspective images directly to wide-angle images is problematic as no account is made for the image distortion. The primary contribution of this thesis is the development of two novel keypoint detectors, and a method of keypoint description, designed for wide-angle images. Both reformulate the Scale- Invariant Feature Transform (SIFT) as an image processing operation on the sphere. As the image captured by any central projection wide-angle camera can be mapped to the sphere, applying these variants to an image on the sphere enables keypoints to be detected in a manner that is invariant to image distortion. Each of the variants is required to find the scale-space representation of an image on the sphere, and they differ in the approaches they used to do this. Extensive experiments using real and synthetically generated wide-angle images are used to validate the two new keypoint detectors and the method of keypoint description. The best of these two new keypoint detectors is applied to vision based localisation tasks including visual odometry and visual place recognition using outdoor wide-angle image sequences. As part of this work, the effect of keypoint coordinate selection on the accuracy of egomotion estimates using the Direct Linear Transform (DLT) is investigated, and a simple weighting scheme is proposed which attempts to account for the uncertainty of keypoint positions during detection. A word reliability metric is also developed for use within a visual ‘bag of words’ approach to place recognition.