39 research outputs found

    Exploring space situational awareness using neuromorphic event-based cameras

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    The orbits around earth are a limited natural resource and one that hosts a vast range of vital space-based systems that support international systems use by both commercial industries, civil organisations, and national defence. The availability of this space resource is rapidly depleting due to the ever-growing presence of space debris and rampant overcrowding, especially in the limited and highly desirable slots in geosynchronous orbit. The field of Space Situational Awareness encompasses tasks aimed at mitigating these hazards to on-orbit systems through the monitoring of satellite traffic. Essential to this task is the collection of accurate and timely observation data. This thesis explores the use of a novel sensor paradigm to optically collect and process sensor data to enhance and improve space situational awareness tasks. Solving this issue is critical to ensure that we can continue to utilise the space environment in a sustainable way. However, these tasks pose significant engineering challenges that involve the detection and characterisation of faint, highly distant, and high-speed targets. Recent advances in neuromorphic engineering have led to the availability of high-quality neuromorphic event-based cameras that provide a promising alternative to the conventional cameras used in space imaging. These cameras offer the potential to improve the capabilities of existing space tracking systems and have been shown to detect and track satellites or ‘Resident Space Objects’ at low data rates, high temporal resolutions, and in conditions typically unsuitable for conventional optical cameras. This thesis presents a thorough exploration of neuromorphic event-based cameras for space situational awareness tasks and establishes a rigorous foundation for event-based space imaging. The work conducted in this project demonstrates how to enable event-based space imaging systems that serve the goals of space situational awareness by providing accurate and timely information on the space domain. By developing and implementing event-based processing techniques, the asynchronous operation, high temporal resolution, and dynamic range of these novel sensors are leveraged to provide low latency target acquisition and rapid reaction to challenging satellite tracking scenarios. The algorithms and experiments developed in this thesis successfully study the properties and trade-offs of event-based space imaging and provide comparisons with traditional observing methods and conventional frame-based sensors. The outcomes of this thesis demonstrate the viability of event-based cameras for use in tracking and space imaging tasks and therefore contribute to the growing efforts of the international space situational awareness community and the development of the event-based technology in astronomy and space science applications

    Measuring knowledge sharing processes through social network analysis within construction organisations

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    The construction industry is a knowledge intensive and information dependent industry. Organisations risk losing valuable knowledge, when the employees leave them. Therefore, construction organisations need to nurture opportunities to disseminate knowledge through strengthening knowledge-sharing networks. This study aimed at evaluating the formal and informal knowledge sharing methods in social networks within Australian construction organisations and identifying how knowledge sharing could be improved. Data were collected from two estimating teams in two case studies. The collected data through semi-structured interviews were analysed using UCINET, a Social Network Analysis (SNA) tool, and SNA measures. The findings revealed that one case study consisted of influencers, while the other demonstrated an optimal knowledge sharing structure in both formal and informal knowledge sharing methods. Social networks could vary based on the organisation as well as the individuals’ behaviour. Identifying networks with specific issues and taking steps to strengthen networks will enable to achieve optimum knowledge sharing processes. This research offers knowledge sharing good practices for construction organisations to optimise their knowledge sharing processes

    The 45th Australasian Universities Building Education Association Conference: Global Challenges in a Disrupted World: Smart, Sustainable and Resilient Approaches in the Built Environment, Conference Proceedings, 23 - 25 November 2022, Western Sydney University, Kingswood Campus, Sydney, Australia

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    This is the proceedings of the 45th Australasian Universities Building Education Association (AUBEA) conference which will be hosted by Western Sydney University in November 2022. The conference is organised by the School of Engineering, Design, and Built Environment in collaboration with the Centre for Smart Modern Construction, Western Sydney University. This year’s conference theme is “Global Challenges in a Disrupted World: Smart, Sustainable and Resilient Approaches in the Built Environment”, and expects to publish over a hundred double-blind peer review papers under the proceedings

    32. Forum Bauinformatik 2021

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    Das Forum Bauinformatik ist eine jährlich stattfindende Tagung und ein wichtiger Bestandteil der Bauinformatik im deutschsprachigen Raum. Insbesondere Nachwuchswissenschaftlerinnen und -wissenschaftlern bietet es die Möglichkeit, ihre Forschungsarbeiten zu präsentieren, Problemstellungen fachspezifisch zu diskutieren und sich über den neuesten Stand der Forschung zu informieren. Es bietet sich ausgezeichnete Gelegenheit, in die wissenschaftliche Gemeinschaft im Bereich der Bauinformatik einzusteigen und Kontakte mit anderen Forschenden zu knüpfen

    Preface

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    Guidelines for the use of flow cytometry and cell sorting in immunological studies (second edition)

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    These guidelines are a consensus work of a considerable number of members of the immunology and flow cytometry community. They provide the theory and key practical aspects of flow cytometry enabling immunologists to avoid the common errors that often undermine immunological data. Notably, there are comprehensive sections of all major immune cell types with helpful Tables detailing phenotypes in murine and human cells. The latest flow cytometry techniques and applications are also described, featuring examples of the data that can be generated and, importantly, how the data can be analysed. Furthermore, there are sections detailing tips, tricks and pitfalls to avoid, all written and peer-reviewed by leading experts in the field, making this an essential research companion

    Insect-inspired visual navigation on-board an autonomous robot: real-world routes encoded in a single layer network

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    Insect-Inspired models of visual navigation, that operate by scanning for familiar views of the world, have been shown to be capable of robust route navigation in simulation. These familiarity-based navigation algorithms operate by training an artificial neural network (ANN) with views from a training route, so that it can then output a familiarity score for any new view. In this paper we show that such an algorithm – with all computation performed on a small low-power robot – is capable of delivering reliable direction information along real-world outdoor routes, even when scenes contain few local landmarks and have high-levels of noise (from variable lighting and terrain). Indeed, routes can be precisely recapitulated and we show that the required computation and storage does not increase with the number of training views. Thus the ANN provides a compact representation of the knowledge needed to traverse a route. In fact, rather than losing information, there are instances where the use of an ANN ameliorates the problems of sub optimal paths caused by tortuous training routes. Our results suggest the feasibility of familiarity-based navigation for long-range autonomous visual homing
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