Robots as a Social Group: Implications for Human-Robot Interaction. This Project aims to identify psychological factors that can limit the acceptance of robots in the home and workplace. As robots become more pervasive in everyday life, they are also likely to elicit fear, rejection, and even damage. The significance of the Project lies in its social neuroscientific approach to promoting better human-robot interaction by considering robots as a social group. Expect outcomes include theory develo ....Robots as a Social Group: Implications for Human-Robot Interaction. This Project aims to identify psychological factors that can limit the acceptance of robots in the home and workplace. As robots become more pervasive in everyday life, they are also likely to elicit fear, rejection, and even damage. The significance of the Project lies in its social neuroscientific approach to promoting better human-robot interaction by considering robots as a social group. Expect outcomes include theory development about human and robot intergroup acceptance, enhanced institutional and international collaborations, and much needed psychological knowledge for robot designers. Benefits include a detailed understanding of how to increase the acceptance of robots in a wide variety of fields.Read moreRead less
SenShaMart: A Trusted Internet of Things Marketplace for Sensor Sharing. This project aims to devise a novel Internet of Things (IoT) sensor sharing marketplace that permits IoT applications to discover, integrate, and pay for any IoT sensor data that is made available by other parties. The project will devise highly-scalable sensor classification, query processing, and transactions solutions and incorporate them in a pair of novel blockchains that work in tandem to securely manage all the infor ....SenShaMart: A Trusted Internet of Things Marketplace for Sensor Sharing. This project aims to devise a novel Internet of Things (IoT) sensor sharing marketplace that permits IoT applications to discover, integrate, and pay for any IoT sensor data that is made available by other parties. The project will devise highly-scalable sensor classification, query processing, and transactions solutions and incorporate them in a pair of novel blockchains that work in tandem to securely manage all the information and contracts needed by IoT applications to discover, integrate, pay, and use sensors provided by another parties. These IoT advancements will provide significant economic, environmental, and social benefits via making low-cost and immediate sensing available across the world.Read moreRead less
Securing Web-based Services by Policy Coherence and Proof-checking. This project aims to develop a provably correct cybersecurity system for workflows, which enables organizations to provide flexible and more secure web-based services and business communication. The project expects to generate new knowledge, theoretic advancement and result in new technologies in the areas of internet of things and cybersecurity. The expected outcomes include a software tool with documentation, which helps organ ....Securing Web-based Services by Policy Coherence and Proof-checking. This project aims to develop a provably correct cybersecurity system for workflows, which enables organizations to provide flexible and more secure web-based services and business communication. The project expects to generate new knowledge, theoretic advancement and result in new technologies in the areas of internet of things and cybersecurity. The expected outcomes include a software tool with documentation, which helps organisations achieve operational excellence and security, and maintain a trusted environment for end users. This system will provide significant economic and commercial benefits to business and end users with highly secured web-services and improved productivity through a coherent framework and proof-checked workflows.Read moreRead less
Discontinued Use of Social Media: Dichotomy of Rational & Emotional Choices. This project aims to gain a better understanding of discontinued use of social media. For businesses and governments, social media serves as a dynamic channel for engagement, value co-creation, and business analytics marketing that is lost when users choose to discontinue its use. This project will generate new knowledge of rational and emotional decision criteria, enabling design features of social media, and their com ....Discontinued Use of Social Media: Dichotomy of Rational & Emotional Choices. This project aims to gain a better understanding of discontinued use of social media. For businesses and governments, social media serves as a dynamic channel for engagement, value co-creation, and business analytics marketing that is lost when users choose to discontinue its use. This project will generate new knowledge of rational and emotional decision criteria, enabling design features of social media, and their complex effects on discontinued use of social media. The expected outcome of this project is an integrated theory of social media discontinuance. The project findings provide significant benefits, such as strategic capabilities and actionable knowledge for businesses and governments to mitigate social media discontinued use.Read moreRead less
A Novel Approach to Semi-Supervised Statistical Machine Learning. Recent successes in the construction of classifiers for making diagnoses and predictions are due in part to their using much data labelled with respect to their class of origin. But typically there are little labelled data but plentiful unlabelled data. The goal of semi-supervised learning (SSL) is to leverage large amounts of unlabelled data to improve the performance using only small labelled datasets and so SSL is of paramount ....A Novel Approach to Semi-Supervised Statistical Machine Learning. Recent successes in the construction of classifiers for making diagnoses and predictions are due in part to their using much data labelled with respect to their class of origin. But typically there are little labelled data but plentiful unlabelled data. The goal of semi-supervised learning (SSL) is to leverage large amounts of unlabelled data to improve the performance using only small labelled datasets and so SSL is of paramount importance to applications where it is expensive or impractical to obtain much labelled data. The project is to develop a novel SSL approach that adopts a missingness mechanism for the missing labels to build a classifier that not only improves accuracy but it can be greater than if the missing labels were known.
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Design and verification of correct, efficient and secure concurrent systems. This project aims to provide methods for the design and verification of correct, secure and efficient concurrent software that are scalable and mechanised. Computers with multiple processors are now the norm and are used in a wide range of safety, security and mission critical software applications such as transport, health and infrastructure. These multi-core architectures have the potential to lead to important effici ....Design and verification of correct, efficient and secure concurrent systems. This project aims to provide methods for the design and verification of correct, secure and efficient concurrent software that are scalable and mechanised. Computers with multiple processors are now the norm and are used in a wide range of safety, security and mission critical software applications such as transport, health and infrastructure. These multi-core architectures have the potential to lead to important efficiency gains, but can introduce complex and error-prone behaviours that cannot be managed using traditional software development approaches. This project will produce better, scalable and mechanised methods for the design and verification of such software which is expected to reduce the prevalence of failures in efficient, modern software.Read moreRead less
Learning Robotic Navigation and Interaction from Object-based Semantic Maps. Our project aims to develop new learning algorithms that enable robots to perform high-complexity tasks that are currently impossible. Compared to existing methods that rely on low-level sensor data, we aim to achieve this by learning from a high-level graph representation of the environment that captures semantics, affordances, and geometry. The outcome would be robots capable of using human instructions to efficiently ....Learning Robotic Navigation and Interaction from Object-based Semantic Maps. Our project aims to develop new learning algorithms that enable robots to perform high-complexity tasks that are currently impossible. Compared to existing methods that rely on low-level sensor data, we aim to achieve this by learning from a high-level graph representation of the environment that captures semantics, affordances, and geometry. The outcome would be robots capable of using human instructions to efficiently learn complex interaction and navigation behaviours that transfer to unseen environments. Our research should benefit new applications in domains of economic and societal importance that are currently too complex, unsafe, and uncertain for robot assistants, such as aged care, advanced manufacturing and domestic robotics.Read moreRead less
Stochastic majorization--minimization algorithms for data science. The changing nature of acquisition and storage data has made the process of drawing inference infeasible with traditional statistical and machine learning methods. Modern data are often acquired in real time, in an incremental nature, and are often available in too large a volume to process on conventional machinery. The project proposes to study the family of stochastic majorisation-minimisation algorithms for computation of inf ....Stochastic majorization--minimization algorithms for data science. The changing nature of acquisition and storage data has made the process of drawing inference infeasible with traditional statistical and machine learning methods. Modern data are often acquired in real time, in an incremental nature, and are often available in too large a volume to process on conventional machinery. The project proposes to study the family of stochastic majorisation-minimisation algorithms for computation of inferential quantities in an incremental manner. The proposed stochastic algorithms encompass and extend upon a wide variety of current algorithmic frameworks for fitting statistical and machine learning models, and can be used to produce feasible and practical algorithms for complex models, both current and future.
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Augmented Sociality: Enabling a Socialised Experience of Augmented Reality. This project will explore new socialised uses of Augmented Reality (AR) that expand creativity, social relations, and participation. We seek to better understand how AR content can be leveraged by people to create their own new ways of learning, collaborating, and relating with each other. To do so we will study and prototype new tools and platforms to allow non-experts to create their own AR media. We aim to enable peop ....Augmented Sociality: Enabling a Socialised Experience of Augmented Reality. This project will explore new socialised uses of Augmented Reality (AR) that expand creativity, social relations, and participation. We seek to better understand how AR content can be leveraged by people to create their own new ways of learning, collaborating, and relating with each other. To do so we will study and prototype new tools and platforms to allow non-experts to create their own AR media. We aim to enable people of all ages, education, and background, to imagine and create, and not just passively consume, AR contents, services, and applications. We will generate new applications of AR, a new platform to collaboratively create these applications, and a new theory of 'Augmented Sociality' to guide AR design.
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Investigating professional learning lives in the digital evolution of work. This project aims to investigate learning practices of professionals working in professions effected by digitalisation. The project expects to generate new knowledge about how professionals’ learning practices shape and are being shaped by evolving work practices. Expected outcomes of the project include new conceptual thinking about professional learning, and a contemporary and nuanced evidence base to inform innovative ....Investigating professional learning lives in the digital evolution of work. This project aims to investigate learning practices of professionals working in professions effected by digitalisation. The project expects to generate new knowledge about how professionals’ learning practices shape and are being shaped by evolving work practices. Expected outcomes of the project include new conceptual thinking about professional learning, and a contemporary and nuanced evidence base to inform innovative teaching and learning solutions for individuals, workplaces and education providers; particularly higher education. This project should provide significant benefits for a national policy on lifelong learning to address Australia’s agile skills development needs.
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