Multi-criteria optimization of group replacement schedules for distributed water pipeline assets

This thesis presents a multi-criteria optimisation study of group replacement schedules for water pipelines, which is a capital-intensive and service critical decision. A new mathematical model was developed, which minimises total replacement costs while maintaining a satisfactory level of services. The research outcomes are expected to enrich the body of knowledge of multi-criteria decision optimisation, where group scheduling is required. The model has the potential to optimise replacement planning for other types of linear asset networks resulting in bottom-line benefits for end users and communities. The results of a real case study show that the new model can effectively reduced the total costs and service interruptions.

A stepped-wedge cluster randomised controlled trial for evaluating rates of falls among inpatients in aged care rehabilitation units receiving tailored multimedia education in addition to usual care : a trial protocol

Introduction Falls are the most frequent adverse event reported in hospitals. Approximately 30% of in-hospital falls lead to an injury and up to 2% result in a fracture. A large randomised trial found that a trained health professional providing individualised falls prevention education to older inpatients reduced falls in a cognitively intact subgroup. This study aims to investigate whether this efficacious intervention can reduce falls and be clinically useful and cost-effective when delivered in the real-life clinical environment. Methods A stepped-wedge cluster randomised trial will be used across eight subacute units (clusters) which will be randomised to one of four dates to start the intervention. Usual care on these units includes patient's screening, assessment and implementation of individualised falls prevention strategies, ongoing staff training and environmental strategies. Patients with better levels of cognition (Mini-Mental State Examination >23/30) will receive the individualised education from a trained health professional in addition to usual care while patient's feedback received during education sessions will be provided to unit staff. Unit staff will receive training to assist in intervention delivery and to enhance uptake of strategies by patients. Falls data will be collected by two methods: case note audit by research assistants and the hospital falls reporting system. Cluster-level data including patient's admissions, length of stay and diagnosis will be collected from hospital systems. Data will be analysed allowing for correlation of outcomes (clustering) within units. An economic analysis will be undertaken which includes an incremental cost-effectiveness analysis. Ethics and dissemination The study was approved by The University of Notre Dame Australia Human Research Ethics Committee and local hospital ethics committees. Results The results will be disseminated through local site networks, and future funding and delivery of falls prevention programmes within WA Health will be informed. Results will also be disseminated through peer-reviewed publications and medical conferences.

Non-contact laser-scanning confocal microscopy of the human cornea in vivo

PURPOSE To investigate the utility of using non-contact laser-scanning confocal microscopy (NC-LSCM), compared with the more conventional contact laser-scanning confocal microscopy (C-LSCM), for examining corneal substructures in vivo. METHODS An attempt was made to capture representative images from the tear film and all layers of the cornea of a healthy, 35 year old female, using both NC-LSCM and C-LSCM, on separate days. RESULTS Using NC-LSCM, good quality images were obtained of the tear film, stroma, and a section of endothelium, but the corneal depth of the images of these various substructures could not be ascertained. Using C-LSCM, good quality, full-field images were obtained of the epithelium, subbasal nerve plexus, stroma, and endothelium, and the corneal depth of each of the captured images could be ascertained. CONCLUSIONS NC-LSCM may find general use for clinical examination of the tear film, stroma and endothelium, with the caveat that the depth of stromal images cannot be determined when using this technique. This technique also facilitates image capture of oblique sections of multiple corneal layers. The inability to clearly and consistently image thin corneal substructures - such as the tear film, subbasal nerve plexus and endothelium - is a key limitation of NC-LSCM.

A reciprocal collaborative method using relevance feedback and feature importance

In a people-to-people matching systems, filtering is widely applied to find the most suitable matches. The results returned are either too many or only a few when the search is generic or specific respectively. The use of a sophisticated recommendation approach becomes necessary. Traditionally, the object of recommendation is the item which is inanimate. In online dating systems, reciprocal recommendation is required to suggest a partner only when the user and the recommended candidate both are satisfied. In this paper, an innovative reciprocal collaborative method is developed based on the idea of similarity and common neighbors, utilizing the information of relevance feedback and feature importance. Extensive experiments are carried out using data gathered from a real online dating service. Compared to benchmarking methods, our results show the proposed method can achieve noticeable better performance.

Objectifying the Subjective : Assessment and Feedback in Creative Arts Studio Learning and Teaching

This paper examines the Assessment and Feedback aspects of Studio Teaching as Creative Arts pedagogy. Prompted by USQ’s newly offered Bachelor of Creative Arts (BCA), the author has developed an Assessment Matrix specifically designed to satisfy a number of imperatives, including: • ‘objectifying’ the subjective aspects of creative practice as assessable coursework/research • providing the means by which accurate, detailed, personalised and confidential feedback may be provided to students individually • providing consistent, accurate, meaningful assessment records for student, lecturer, and institution • ensuring consistency, continuity, and transparency of assessment processes and records to satisfy quality audits • minimising marking and assessment time, whilst maximising assessment integrity and depth • requiring only basic level skills and knowledge of a computer application already in common use (Microsoft Excel) • adaptability to a range of creative courses ‐ across disciplines This Assessment Matrix has been in development (and trialled) since January 2009.

A high performance feedback active noise control system

In many active noise control (ANC) applications, an online secondary path modelling method that uses a white noise as a training signal is required. This paper proposes a new feedback ANC system. Here we modified both the FxLMS and the VSS-LMS algorithms to raised noise attenuation and modelling accuracy for the overall system. The proposed algorithm stops injection of the white noise at the optimum point and reactivate the injection during the operation, if needed, to maintain performance of the system. Preventing continuous injection of the white noise increases the performance of the proposed method significantly and makes it more desirable for practical ANC systems. Computer simulation results shown in this paper indicate effectiveness of the proposed method.

Motivating domestic energy conservation through comparative feedback in mobile applications and social networking sites

The progress of technology has led to the increased adoption of energy monitors among household energy consumers. While the monitors available on the market deliver real-time energy usage feedback to the consumer, the form of this data is usually unengaging and mundane. Moreover, it fails to address consumers with different motivations and needs to save and compare energy. This master‟s thesis project presents a study that seeks to inform design guidelines for differently motivated energy consumers. The focus of the research is on comparative feedback supported by a community of energy consumers. In particular, the discussed comparative feedback types are explanatory comparison, temporal self-comparison, norm comparison, one-on-one comparison and ranking, whereby the last three support exploring the potential of socialising energy-related feedback in social networking sites, such as Facebook. These feedback types were integrated in EnergyWiz – a mobile application that enables users to compare with their past performance, neighbours, contacts from social networking sites and other EnergyWiz users. The application was developed through a theory-driven approach and evaluated in personal, semi-structured interviews which provided insights on how motivation-related comparative feedback should be designed. It was also employed in expert focus group discussions which resulted in defining opportunities and challenges before mobile, social energy monitors. The findings have unequivocally shown that users with different motivations to compare and to conserve energy have different preferences for comparative feedback types and design. It was established that one of the most influential factors determining design factors is the people users compare to. In addition, the research found that even simple communication strategies in Facebook, such as wall posts and groups can contribute to engagement with energy conservation practices. The concept of mobility of the application was evaluated as positive since it provides place and time-independent access to the energy consumption data.

Prevention of Alcohol-Related Crime and Trauma (PACT) : brief interventions in routine care pathway – a study protocol

Background Globally, alcohol-related injuries cause millions of deaths and huge economic loss each year . The incidence of facial (jawbone) fractures in the Northern Territory of Australia is second only to Greenland, due to a strong involvement of alcohol in its aetiology, and high levels of alcohol consumption. The highest incidences of alcohol-related trauma in the Territory are observed amongst patients in the Maxillofacial Surgery Unit of the Royal Darwin Hospital. Accordingly, this project aims to introduce screening and brief interventions into this unit, with the aims of changing health service provider practice, improving access to care, and improving patient outcomes. Methods Establishment of Project Governance: The project governance team includes a project manager, project leader, an Indigenous Reference Group (IRG) and an Expert Reference Group (ERG). Development of a best practice pathway: PACT project researchers collaborate with clinical staff to develop a best practice pathway suited to the setting of the surgical unit. The pathway provides clear guidelines for screening, assessment, intervention and referral. Implementation: The developed pathway is introduced to the unit through staff training workshops and associate resources and adapted in response to staff feedback. Evaluation: File audits, post workshop questionnaires and semi-structured interviews are administered. Discussion This project allows direct transfer of research findings into clinical practice and can inform future hospital-based injury prevention strategies.

Laser-radar data fusion with Gaussian Process Implicit Surfaces

This work considers the problem of building high-fidelity 3D representations of the environment from sensor data acquired by mobile robots. Multi-sensor data fusion allows for more complete and accurate representations, and for more reliable perception, especially when different sensing modalities are used. In this paper, we propose a thorough experimental analysis of the performance of 3D surface reconstruction from laser and mm-wave radar data using Gaussian Process Implicit Surfaces (GPIS), in a realistic field robotics scenario. We first analyse the performance of GPIS using raw laser data alone and raw radar data alone, respectively, with different choices of covariance matrices and different resolutions of the input data. We then evaluate and compare the performance of two different GPIS fusion approaches. The first, state-of-the-art approach directly fuses raw data from laser and radar. The alternative approach proposed in this paper first computes an initial estimate of the surface from each single source of data, and then fuses these two estimates. We show that this method outperforms the state of the art, especially in situations where the sensors react differently to the targets they perceive.

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.

Laser-to-radar sensing redundancy for resilient perception in adverse environmental conditions

This paper presents an approach to promote the integrity of perception systems for outdoor unmanned ground vehicles (UGV) operating in challenging environmental conditions (presence of dust or smoke). The proposed technique automatically evaluates the consistency of the data provided by two sensing modalities: a 2D laser range finder and a millimetre-wave radar, allowing for perceptual failure mitigation. Experimental results, obtained with a UGV operating in rural environments, and an error analysis validate the approach.

Reliable automatic camera-laser calibration

Camera-laser calibration is necessary for many robotics and computer vision applications. However, existing calibration toolboxes still require laborious effort from the operator in order to achieve reliable and accurate results. This paper proposes algorithms that augment two existing trustful calibration methods with an automatic extraction of the calibration object from the sensor data. The result is a complete procedure that allows for automatic camera-laser calibration. The first stage of the procedure is automatic camera calibration which is useful in its own right for many applications. The chessboard extraction algorithm it provides is shown to outperform openly available techniques. The second stage completes the procedure by providing automatic camera-laser calibration. The procedure has been verified by extensive experimental tests with the proposed algorithms providing a major reduction in time required from an operator in comparison to manual methods.

Laser-camera data discrepancies and reliable perception in outdoor robotics

This work aims to promote integrity in autonomous perceptual systems, with a focus on outdoor unmanned ground vehicles equipped with a camera and a 2D laser range finder. A method to check for inconsistencies between the data provided by these two heterogeneous sensors is proposed and discussed. First, uncertainties in the estimated transformation between the laser and camera frames are evaluated and propagated up to the projection of the laser points onto the image. Then, for each pair of laser scan-camera image acquired, the information at corners of the laser scan is compared with the content of the image, resulting in a likelihood of correspondence. The result of this process is then used to validate segments of the laser scan that are found to be consistent with the image, while inconsistent segments are rejected. Experimental results illustrate how this technique can improve the reliability of perception in challenging environmental conditions, such as in the presence of airborne dust.