Safety leaders' perceptions of safety culture in a large Australian construction organisation

Safety culture in the construction industry is a growing research area. The unique nature of construction industry works – being project-based, varying in size and focus, and relying on a highly transient subcontractor workforce – means that safety culture initiatives cannot be easily translated from other industries. This paper reports on the first study in a three year collaborative industry and university research project focusing on safety culture practices and development in one of Australia’s largest global construction organisations. The first round of a modified Delphi method is reported, and describes the insights gained from 41 safety leaders’ perceptions and understandings of safety culture within the organisation. In-depth, semi-structured interviews were conducted, and will be followed by a quantitative perception survey with the same sample. Participants included Senior Executives, Corporate Managers, Project Managers, Safety Managers and Site Supervisors. Leaders’ definitions and descriptions of safety culture were primarily action-oriented and some confusion was evident due to the sometimes implicit nature of culture in organisations. Leadership was identified as a key factor for positive safety culture in the organisation, and there was an emphasis on leaders demonstrating commitment to safety, and being visible to the project-based workforce. Barriers to safety culture improvement were also identified, with managers raising diverse issues such as the transient subcontractor workforce and the challenge of maintaining safety as a priority in the absence of safety incidents, under high production pressures. This research is unique in that it derived safety culture descriptions from key stakeholders within the organisation, as opposed to imposing traditional conceptualisations of safety culture that are not customised for the organisation or the construction industry more broadly. This study forms the foundation for integrating safety culture theory and practice in the construction industry, and will be extended upon in future studies within the research program.

Monitoring mesenchymal stem cell cultures using image processing and pattern recognition techniques

Stem cells have attracted tremendous interest in recent times due to their promise in providing innovative new treatments for a great range of currently debilitating diseases. This is due to their potential ability to regenerate and repair damaged tissue, and hence restore lost body function, in a manner beyond the body's usual healing process. Bone marrow-derived mesenchymal stem cells or bone marrow stromal cells are one type of adult stem cells that are of particular interest. Since they are derived from a living human adult donor, they do not have the ethical issues associated with the use of human embryonic stem cells. They are also able to be taken from a patient or other donors with relative ease and then grown readily in the laboratory for clinical application. Despite the attractive properties of bone marrow stromal cells, there is presently no quick and easy way to determine the quality of a sample of such cells. Presently, a sample must be grown for weeks and subject to various time-consuming assays, under the direction of an expert cell biologist, to determine whether it will be useful. Hence there is a great need for innovative new ways to assess the quality of cell cultures for research and potential clinical application. The research presented in this thesis investigates the use of computerised image processing and pattern recognition techniques to provide a quicker and simpler method for the quality assessment of bone marrow stromal cell cultures. In particular, aim of this work is to find out whether it is possible, through the use of image processing and pattern recognition techniques, to predict the growth potential of a culture of human bone marrow stromal cells at early stages, before it is readily apparent to a human observer. With the above aim in mind, a computerised system was developed to classify the quality of bone marrow stromal cell cultures based on phase contrast microscopy images. Our system was trained and tested on mixed images of both healthy and unhealthy bone marrow stromal cell samples taken from three different patients. This system, when presented with 44 previously unseen bone marrow stromal cell culture images, outperformed human experts in the ability to correctly classify healthy and unhealthy cultures. The system correctly classified the health status of an image 88% of the time compared to an average of 72% of the time for human experts. Extensive training and testing of the system on a set of 139 normal sized images and 567 smaller image tiles showed an average performance of 86% and 85% correct classifications, respectively. The contributions of this thesis include demonstrating the applicability and potential of computerised image processing and pattern recognition techniques to the task of quality assessment of bone marrow stromal cell cultures. As part of this system, an image normalisation method has been suggested and a new segmentation algorithm has been developed for locating cell regions of irregularly shaped cells in phase contrast images. Importantly, we have validated the efficacy of both the normalisation and segmentation method, by demonstrating that both methods quantitatively improve the classification performance of subsequent pattern recognition algorithms, in discriminating between cell cultures of differing health status. We have shown that the quality of a cell culture of bone marrow stromal cells may be assessed without the need to either segment individual cells or to use time-lapse imaging. Finally, we have proposed a set of features, that when extracted from the cell regions of segmented input images, can be used to train current state of the art pattern recognition systems to predict the quality of bone marrow stromal cell cultures earlier and more consistently than human experts.

Community-based protest against construction projects : a case study of movement continuity

Community-based activism against proposed construction projects is growing. Many protests are poorly managed and escalate into long-term and sometimes acrimonious disputes which damage communities, firms and the construction industry as a whole. Using a thematic storytelling approach which draws on ethnographic method, within a single case study framework, new insights into the social forces that shape and sustain community-based protest against construction projects are provided. A conceptual model of protest movement continuity is presented which highlights the factors that sustain protest continuity over time. The model illustrates how social contagion leads to common community perceptions of development risk and opportunity, to a positive internalization of collective values and identity, to a strategic utilization of social capital and an awareness of the need to manage the emotional dynamics of protest through mechanisms such as symbolic artefacts.

Relational contracting and its efficacy of project outcomes in the Australian construction industry

The Australian construction industry is characterized as being a competitive and risky business environment due to lack of cooperation, insufficient trust, ineffective communication and adversarial relationships which are likely lead to poor project performance. Relational contracting (RC) is advocated by literature as an innovative approach to improve the procurement process in the construction industry. Various studies have collectively added to the current knowledge of known RC norms, but there seem to be little effort on investigating the determinants of RC and its efficacy on project outcomes. In such circumstances, there is a lack of evidence and explanation on the manner on how these issues lead to different performance. Simultaneously, the New Engineering Contract (NEC) that embraced the concept of RC is seen as a modern way of contracting and also considered as one of the best approaches to the perennial problem of improving adversarial relationships within the industry. The reality of practice of RC in Australia is investigated through the lens of the NEC. A synthesis of literature views on the concept, processes and tools of RC is first conducted to develop the framework of RC.

Matrix regularization techniques for online multitask learning

In this paper we examine the problem of prediction with expert advice in a setup where the learner is presented with a sequence of examples coming from different tasks. In order for the learner to be able to benefit from performing multiple tasks simultaneously, we make assumptions of task relatedness by constraining the comparator to use a lesser number of best experts than the number of tasks. We show how this corresponds naturally to learning under spectral or structural matrix constraints, and propose regularization techniques to enforce the constraints. The regularization techniques proposed here are interesting in their own right and multitask learning is just one application for the ideas. A theoretical analysis of one such regularizer is performed, and a regret bound that shows benefits of this setup is reported.

The desire for the construction industry to move towards lifecycle carbon emissions analysis

A significant reduction in carbon emissions is a global mission and the construction industry has an indispensable role to play as a major carbon dioxide (CO2) generator. Over the years, various building environmental assessment (BEA) models and concepts have been developed to promote environmentally responsible design and construction. However, limited attention has been placed on assessing and benchmarking the carbon emitted throughout the lifecycle of building facilities. This situation could undermine the construction industry’s potential to reduce its dependence on raw materials, recognise the negative impacts of producing new materials, and intensify the recycle and reuse process. In this paper, current BEA approaches adopted by the construction industry are first introduced. The focus of these models and concepts is then examined. Following a brief review of lifecycle analysis, the boundary in which a lifecycle carbon emission analysis should be set for a construction project is identified. The paper concludes by highlighting the potential barriers of applying lifecycle carbon emissions analysis in the construction industry. It is proposed that lifecycle carbon emission analysis can be integrated with existing BEA models to provide a more comprehensive and accurate evaluation on the cradle-to-grave environmental performance of a construction facility. In doing so, this can assist owners and clients to identify the optimum solution to maximise emissions reduction opportunities.

Navigating, recognizing and describing urban spaces with vision and lasers

In this paper we describe a body of work aimed at extending the reach of mobile navigation and mapping. We describe how running topological and metric mapping and pose estimation processes concurrently, using vision and laser ranging, has produced a full six-degree-of-freedom outdoor navigation system. It is capable of producing intricate three-dimensional maps over many kilometers and in real time. We consider issues concerning the intrinsic quality of the built maps and describe our progress towards adding semantic labels to maps via scene de-construction and labeling. We show how our choices of representation, inference methods and use of both topological and metric techniques naturally allow us to fuse maps built from multiple sessions with no need for manual frame alignment or data association.