Visualisation of latent DNA. This project aims to deliver a proof-of-concept that allows visualisation of invisible DNA (latent DNA) into a quick, inexpensive and practical DNA collection method that will lead to DNA evidence being available in more cases. It will build upon a proof-of-concept method ready for transferal to forensic casework. This will allow DNA evidence recovery technicians to improve their hit rate in recovering latent DNA from real crime items, leading to more informative DNA ....Visualisation of latent DNA. This project aims to deliver a proof-of-concept that allows visualisation of invisible DNA (latent DNA) into a quick, inexpensive and practical DNA collection method that will lead to DNA evidence being available in more cases. It will build upon a proof-of-concept method ready for transferal to forensic casework. This will allow DNA evidence recovery technicians to improve their hit rate in recovering latent DNA from real crime items, leading to more informative DNA profiles. Crime items that currently yield no genetic information will now be informative, assisting investigations of serious crimes or terrorist incidents.Read moreRead less
Dynamic prediction models in Australian rules football using real time performance statistics. The study is a collaborative venture with Champion Data, the Australian leader in the collection and transmission of real time sporting data, and official provider of the Australian Football League (AFL) statistics. The aim is to develop a real time on line predictive model for AFL football. The model will use the statistics Champion Data collect as the match progresses as inputs to continually updat ....Dynamic prediction models in Australian rules football using real time performance statistics. The study is a collaborative venture with Champion Data, the Australian leader in the collection and transmission of real time sporting data, and official provider of the Australian Football League (AFL) statistics. The aim is to develop a real time on line predictive model for AFL football. The model will use the statistics Champion Data collect as the match progresses as inputs to continually update estimates of the probabilities of various outcomes of interest such as the winner of the match and the margin of victory. The project will assist Champion in their strategic aim to provide an on line form guide.Read moreRead less
Next-generation latent fingermark detection using functional nanomaterials. Next-generation latent fingermark detection using functional nanomaterials. This project aims to develop a nanotechnology-based fingermark detection technique applicable in standard police laboratories and crime scenes. Current methods only detect half the fingermarks on an object, so many criminals are not identified. This project will use silicon oxide nanoparticles with a luminescent dye to target fingermark secretion ....Next-generation latent fingermark detection using functional nanomaterials. Next-generation latent fingermark detection using functional nanomaterials. This project aims to develop a nanotechnology-based fingermark detection technique applicable in standard police laboratories and crime scenes. Current methods only detect half the fingermarks on an object, so many criminals are not identified. This project will use silicon oxide nanoparticles with a luminescent dye to target fingermark secretion components and address interference from substrate chemistries and background luminescence. Moving away from traditional detection methods is expected to improve law enforcement outcomes, as fingermarks that current technologies cannot detect will be visualised for the first time.Read moreRead less
The effective treatment of drug using offenders: the impact of treatment modality, coercion and treatment readiness on criminal recidivism. Drug use is associated with significant health, social, and economic costs. Given the established drug-crime connection and the high rate of relapse among drug-using offenders, the outcomes of this research will assist policymakers in identifying clinically and cost effective approaches to service delivery. Moreover, in view of the debate that surrounds the ....The effective treatment of drug using offenders: the impact of treatment modality, coercion and treatment readiness on criminal recidivism. Drug use is associated with significant health, social, and economic costs. Given the established drug-crime connection and the high rate of relapse among drug-using offenders, the outcomes of this research will assist policymakers in identifying clinically and cost effective approaches to service delivery. Moreover, in view of the debate that surrounds the efficacy of coerced treatment, and the extent to which Australia should follow the United States of America’s lead of mandating treatment for all substance using offenders, the project will test the proposition that compulsory treatment has positive outcomes in terms of reductions in recidivism.Read moreRead less
Australian Laureate Fellowships - Grant ID: FL150100150
Funder
Australian Research Council
Funding Amount
$2,413,112.00
Summary
Bayesian learning for decision making in the big data era. Bayesian learning for decision making in the big data era: This fellowship project aims to develop new techniques in evidence-based learning and decision-making in the big data era. Big data has arrived, and with it a huge global demand for statistical knowledge and skills to analyse these data for improved learning and decision-making. This project will seek to address this need by creating a step-change in knowledge in Bayesian statist ....Bayesian learning for decision making in the big data era. Bayesian learning for decision making in the big data era: This fellowship project aims to develop new techniques in evidence-based learning and decision-making in the big data era. Big data has arrived, and with it a huge global demand for statistical knowledge and skills to analyse these data for improved learning and decision-making. This project will seek to address this need by creating a step-change in knowledge in Bayesian statistics and translating this knowledge to real-world challenges in industry, environment and health. The new big data statistical analysts trained through the project could also create much needed capacity at national and international levels.Read moreRead less
Inverse and related problems in statistics. Modern statistical inverse problems arise in fields from astronomy and biology to engineering and finance. Sometimes the problems involve the analysis of small samples of very high dimensional data, and are central to information aquisition in areas such as genomics and signal analysis. All these topics are of significant national importance, and their solution will bring national and community benefits. In addition, the program to which the proposa ....Inverse and related problems in statistics. Modern statistical inverse problems arise in fields from astronomy and biology to engineering and finance. Sometimes the problems involve the analysis of small samples of very high dimensional data, and are central to information aquisition in areas such as genomics and signal analysis. All these topics are of significant national importance, and their solution will bring national and community benefits. In addition, the program to which the proposal will lead will be used extensively for research training. In Australia, where the demand for research-trained statisticians greatly exceeds supply, this contribution to the nation and the community will be particularly important. Read moreRead less
New and computationally feasible methods of constructing efficient and exact confidence limits from count data. Biological and health science data is commonly in the form of counts. The statistical analysis of such data should be (a) efficient i.e. it should not, in effect, throw away valuable data, (b) exact i.e. it should have precisely known statistical properties and (c) computationally feasible. Kabaila and Lloyd (1997-2001) have proposed and analysed a radically new method of confidence li ....New and computationally feasible methods of constructing efficient and exact confidence limits from count data. Biological and health science data is commonly in the form of counts. The statistical analysis of such data should be (a) efficient i.e. it should not, in effect, throw away valuable data, (b) exact i.e. it should have precisely known statistical properties and (c) computationally feasible. Kabaila and Lloyd (1997-2001) have proposed and analysed a radically new method of confidence limit construction which, for the first time, possesses all of these requirements. The purpose of the project is to establish further theoretical support for the new method, to develop efficient computational algorithms and to write easy-to-use computer programs for its practical use.Read moreRead less
Classification methods for providing personalised and class decisions. This project provides a novel approach to the clustering of multivariate samples on entities in a class that automatically matches the sample clusters across the entities, allowing for inter-sample variation between the samples in a class. The project aims to develop a widely applicable, mixture-model-based framework for the simultaneous clustering of multivariate samples with inter-sample variation in a class and for the mat ....Classification methods for providing personalised and class decisions. This project provides a novel approach to the clustering of multivariate samples on entities in a class that automatically matches the sample clusters across the entities, allowing for inter-sample variation between the samples in a class. The project aims to develop a widely applicable, mixture-model-based framework for the simultaneous clustering of multivariate samples with inter-sample variation in a class and for the matching of the clusters across the entities in the class. The project will use a statistical approach to automatically match the clusters, since the overall mixture model provides a template for the class. It will provide a basis for discriminating between different classes in addition to the identification of atypical data points within a sample and of anomalous samples within a class. Key applications include biological image analysis and the analysis of data in flow cytometry which is one of the fundamental research tools for the life scientist.Read moreRead less
Threshold Decisions in Determining Whether to Prosecute Child Sexual Abuse. The objective of this project is new knowledge about the way police and prosecutors make decisions about the prosecution of child sexual assault that could be used to influence policy and practice. Few cases of child sexual abuse reported to the police ever go to court but recent research in New South Wales for the Royal Commission indicates that the proportion has declined sharply over the last decade or so. This projec ....Threshold Decisions in Determining Whether to Prosecute Child Sexual Abuse. The objective of this project is new knowledge about the way police and prosecutors make decisions about the prosecution of child sexual assault that could be used to influence policy and practice. Few cases of child sexual abuse reported to the police ever go to court but recent research in New South Wales for the Royal Commission indicates that the proportion has declined sharply over the last decade or so. This project aims to examine how police and prosecutors decide which cases proceed and why, and how they confer with each other as well as when and how they consult with complainants and their families. This project plans to also develop and test practice tools and principles for police and prosecutors with expected benefits for both them and the families involved.Read moreRead less
Rapid CYBERNOSE ® detection of illicit drugs and precursor chemicals. Rapid CYBERNOSE ® detection of illicit drugs and precursor chemicals. This project aims to develop a novel biosensor prototype based on CYBERNOSE® technology to rapidly identify volatile traces of illicit drugs and precursor chemicals in concealed environments. The CYBERNOSE® technology employs sensors using the highly sophisticated and sensitive olfactory receptors of microscopic nematode worms linked to an optoelectronic det ....Rapid CYBERNOSE ® detection of illicit drugs and precursor chemicals. Rapid CYBERNOSE ® detection of illicit drugs and precursor chemicals. This project aims to develop a novel biosensor prototype based on CYBERNOSE® technology to rapidly identify volatile traces of illicit drugs and precursor chemicals in concealed environments. The CYBERNOSE® technology employs sensors using the highly sophisticated and sensitive olfactory receptors of microscopic nematode worms linked to an optoelectronic detector. The need for rapid, non-contact screening devices to detect and identify illicit drugs and precursors entering Australia has never been greater. Law enforcement agencies should directly benefit from the capability to more rapidly screen people and cargo, improving efficiency of illicit drug detection and protection of our borders.Read moreRead less