Preventing railway suicide: An open-systems perspective. Preventing railway suicide: An open-systems perspective. This project aims to develop an automated suicide risk detection system to reduce the incidence and impact of railway suicide, which has a devastating effect on victims’ families, station staff, train drivers, emergency workers, and bystanders. This project will use open-systems theory to develop two complementary information systems for more effective detection and reporting of suic ....Preventing railway suicide: An open-systems perspective. Preventing railway suicide: An open-systems perspective. This project aims to develop an automated suicide risk detection system to reduce the incidence and impact of railway suicide, which has a devastating effect on victims’ families, station staff, train drivers, emergency workers, and bystanders. This project will use open-systems theory to develop two complementary information systems for more effective detection and reporting of suicide risk; use these systems to investigate how different situational factors interact with different combinations of service interventions to influence suicide risk; and share the findings to reduce railway suicide in Australia and overseas.Read moreRead less
Unlocking benefits from digital investments. This project aims to address one of the most vexing questions in the management of information systems: how to unlock the value of digital investments. The project expects to develop new theory and evidence on how to achieve meaningful use of information systems at multiple levels of analysis. The project will especially benefit the health sector, and society, by helping health providers and vendors to maximise the value obtained from substantial inve ....Unlocking benefits from digital investments. This project aims to address one of the most vexing questions in the management of information systems: how to unlock the value of digital investments. The project expects to develop new theory and evidence on how to achieve meaningful use of information systems at multiple levels of analysis. The project will especially benefit the health sector, and society, by helping health providers and vendors to maximise the value obtained from substantial investment in digital technologies, and by developing evidence-based policies to optimise digital service delivery.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE240101364
Funder
Australian Research Council
Funding Amount
$445,591.00
Summary
Governing Industrial Data Ecosystems: Open Innovation in a Digital Economy. This project aims to investigate how governance mechanisms incentivise multilateral data-sharing to enable open innovation in industrial data ecosystems. Based on a rigorous multi-method study at ecosystem, firm and managerial levels, a framework of generative open innovation to govern multilateral data sharing will be developed. By addressing data-sharing barriers at all levels, the framework helps create collective val ....Governing Industrial Data Ecosystems: Open Innovation in a Digital Economy. This project aims to investigate how governance mechanisms incentivise multilateral data-sharing to enable open innovation in industrial data ecosystems. Based on a rigorous multi-method study at ecosystem, firm and managerial levels, a framework of generative open innovation to govern multilateral data sharing will be developed. By addressing data-sharing barriers at all levels, the framework helps create collective value at the ecosystem level and capture a portion of that value at the firm and managerial levels. This should enable participants in industrial data ecosystems to share data confidently and unlock the full potential of open innovation for Australia’s digital economy, with estimated benefits of $315bn over the next decade. Read moreRead less
Contextual Behabiour Predictions in Dynamic Mobile E-commerce. The project aims to address behaviour prediction and develop novel techniques and tools for modelling, predicting human behaviours and making effective recommendations based on ubiquitous user behaviour data in mobile e-commerce. The techniques enable multi-source data fusion, context learning and model adaptation, and dynamic recommendation with interpretability ability. Expected outcomes include advances in data analytics theory an ....Contextual Behabiour Predictions in Dynamic Mobile E-commerce. The project aims to address behaviour prediction and develop novel techniques and tools for modelling, predicting human behaviours and making effective recommendations based on ubiquitous user behaviour data in mobile e-commerce. The techniques enable multi-source data fusion, context learning and model adaptation, and dynamic recommendation with interpretability ability. Expected outcomes include advances in data analytics theory and informed decision-making. This provides significant benefits of not only placing Australia in the forefront of exploiting multimodal user behaviour big data in dynamic e-commerce but also transforming Australian government and businesses to intelligent and contextual services adaptive to complex situations.Read moreRead less
Developing an effective defence to cyber-reputation manipulation attacks. This project will develop new technologies for businesses to accurately identify fake internet reviews. Fake reviews, paid for and/or written with malicious intent, can cause irreparable damage to businesses resulting in revenue loss, consumer dissatisfaction or even closure of businesses. However they are difficult to identify, as they continuously evolve to avoid detection and the volume of Internet reviews makes analysi ....Developing an effective defence to cyber-reputation manipulation attacks. This project will develop new technologies for businesses to accurately identify fake internet reviews. Fake reviews, paid for and/or written with malicious intent, can cause irreparable damage to businesses resulting in revenue loss, consumer dissatisfaction or even closure of businesses. However they are difficult to identify, as they continuously evolve to avoid detection and the volume of Internet reviews makes analysis a monumental task. This project will provide advanced tools to detect fake website reviews and a cybersecurity system prototype ready to be used by industry, making Australia a leader in this field and resulting in a safer internet environment for all.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE180100251
Funder
Australian Research Council
Funding Amount
$368,446.00
Summary
Trust-aware internet of things service recommendation. This project aims to develop innovative techniques and tools to recommend Internet of Things resources as services for trustworthy and cost-effective applications. Internet of Things connects billions of physical things over the Web, offering exciting opportunities to improve life quality and reshape human society. The project is expected to underpin innovative applications like smart home, urban computing, and mobile social sensing, which c ....Trust-aware internet of things service recommendation. This project aims to develop innovative techniques and tools to recommend Internet of Things resources as services for trustworthy and cost-effective applications. Internet of Things connects billions of physical things over the Web, offering exciting opportunities to improve life quality and reshape human society. The project is expected to underpin innovative applications like smart home, urban computing, and mobile social sensing, which can significantly contribute to Australian society and the national economy. It also holds the potential to place Australia at the forefront of research and development in the vibrant and growing area of trustworthy Internet of Things.Read moreRead less
Context and Activity Recognition for Personalised Behaviour Recommendation. The Internet of Things (IoT) together with the rising popularity of smartphones opens a new world for many exciting opportunities. The overall goal of this project is to develop new algorithms and data analytical techniques in an IoT environment that can accurately monitor and analyse personalised daily activities on a continuous, real-time basis. The expected result of this project will support many critical application ....Context and Activity Recognition for Personalised Behaviour Recommendation. The Internet of Things (IoT) together with the rising popularity of smartphones opens a new world for many exciting opportunities. The overall goal of this project is to develop new algorithms and data analytical techniques in an IoT environment that can accurately monitor and analyse personalised daily activities on a continuous, real-time basis. The expected result of this project will support many critical applications such as better wellness tracking and lifestyle-related illness prevention, which will be particularly critical to Australia's aging population. This project will also serve as a vehicle to educate and train Australia’s young scholars and engineers.Read moreRead less
Robust Preference Inference from Spatial-Temporal Interaction Networks. This project aims to develop innovative techniques for effectively and efficiently managing user preference profiles from less labelled, sparse and noisy interaction data. A unified novel learning framework along with a set of data analysis techniques are expected to be developed from this project, which will provide a non-intrusive way of conducting predictive analysis on user preference profiling via discovering human expl ....Robust Preference Inference from Spatial-Temporal Interaction Networks. This project aims to develop innovative techniques for effectively and efficiently managing user preference profiles from less labelled, sparse and noisy interaction data. A unified novel learning framework along with a set of data analysis techniques are expected to be developed from this project, which will provide a non-intrusive way of conducting predictive analysis on user preference profiling via discovering human explicit and implicit interest domains. The expected results of this application will not only maintain Australia's leadership in this frontier research area, but also support many important applications that safeguard Australian people and economy such as cyber security, healthcare, and e-Commerce.Read moreRead less
Next Generation Spatial Data Management for Virtual Spatial Systems. This project aims to design novel spatial data retrieval methods for efficient and accurate querying of large datasets with location information. Spatial data is being generated at an unprecedented rate due to the prevalence of mobile devices and ubiquitous connectivity. However, harnessing this data is hampered by outdated and inefficient methods. The project will investigate data retrieval methods that self-optimise for high ....Next Generation Spatial Data Management for Virtual Spatial Systems. This project aims to design novel spatial data retrieval methods for efficient and accurate querying of large datasets with location information. Spatial data is being generated at an unprecedented rate due to the prevalence of mobile devices and ubiquitous connectivity. However, harnessing this data is hampered by outdated and inefficient methods. The project will investigate data retrieval methods that self-optimise for high query efficiency and accuracy, by utilising underlying real-world data patterns. It will enable novel applications for virtual spatial systems with large-scale querying needs, such as spatial digital twins and metaverses, benefiting location-based service providers, urban planners, and emergency management agencies.Read moreRead less