Methods and consequences of suicide attempts among Australian students

Schweitzer et al. previously published a paper in the Australian and New Zealand Journal of Psychiatry which provided prevalence rates on suicidal ideation and behaviour among university students [1]. We wish to provide an update on extensions of our previously published work. In our previous publication we indicated the relatively high percentage of students who reported suicide-related behaviour over the past 12 months (6.6%). This figure is very similar to a more recent study undertaken in the UK where 6% of student respondents reported suicide attempts [2]. As a follow up, we investigated this finding further in studies undertaken in 1994 and 1997 by asking fresh samples of University of Queensland first-year undergraduates who responded positively to the question ‘I have made attempts to kill myself’ (in the past year), to provide additional data relating to the methods employed in their suicide attempts and the consequences following their suicide attempt in terms of level of injury and medical care received...

Channel tracking in SDMA-based multi-user MIMO-OFDM communications systems

Capacity of current and future high data rate wireless communications depend significantly on how well changes in the wireless channel are predicted and tracked. Generally, this can be estimated by transmitting known symbols. However, this increases overheads if the channel varies over time. Given today’s bandwidth demand and the increased necessity for mobile wireless devices, the contributions of this research are very significant. This study has developed a novel and efficient channel tracking algorithm that can recursively update the channel estimation for wireless broadband communications reducing overheads, therefore increasing the speed of wireless communication systems.

An efficient proactive route maintenance process for reliable data transmissions in sensor networks

For industrial wireless sensor networks, maintaining the routing path for a high packet delivery ratio is one of the key objectives in network operations. It is important to both provide the high data delivery rate at the sink node and guarantee a timely delivery of the data packet at the sink node. Most proactive routing protocols for sensor networks are based on simple periodic updates to distribute the routing information. A faulty link causes packet loss and retransmission at the source until periodic route update packets are issued and the link has been identified as broken. We propose a new proactive route maintenance process where periodic update is backed-up with a secondary layer of local updates repeating with shorter periods for timely discovery of broken links. Proposed route maintenance scheme improves reliability of the network by decreasing the packet loss due to delayed identification of broken links. We show by simulation that proposed mechanism behaves better than the existing popular routing protocols (AODV, AOMDV and DSDV) in terms of end-to-end delay, routing overhead, packet reception ratio.

Building adaptable agent-based models – application to the electricity distribution network

Agent-based modelling (ABM), like other modelling techniques, is used to answer specific questions from real world systems that could otherwise be expensive or impractical. Its recent gain in popularity can be attributed to some degree to its capacity to use information at a fine level of detail of the system, both geographically and temporally, and generate information at a higher level, where emerging patterns can be observed. This technique is data-intensive, as explicit data at a fine level of detail is used and it is computer-intensive as many interactions between agents, which can learn and have a goal, are required. With the growing availability of data and the increase in computer power, these concerns are however fading. Nonetheless, being able to update or extend the model as more information becomes available can become problematic, because of the tight coupling of the agents and their dependence on the data, especially when modelling very large systems. One large system to which ABM is currently applied is the electricity distribution where thousands of agents representing the network and the consumers’ behaviours are interacting with one another. A framework that aims at answering a range of questions regarding the potential evolution of the grid has been developed and is presented here. It uses agent-based modelling to represent the engineering infrastructure of the distribution network and has been built with flexibility and extensibility in mind. What distinguishes the method presented here from the usual ABMs is that this ABM has been developed in a compositional manner. This encompasses not only the software tool, which core is named MODAM (MODular Agent-based Model) but the model itself. Using such approach enables the model to be extended as more information becomes available or modified as the electricity system evolves, leading to an adaptable model. Two well-known modularity principles in the software engineering domain are information hiding and separation of concerns. These principles were used to develop the agent-based model on top of OSGi and Eclipse plugins which have good support for modularity. Information regarding the model entities was separated into a) assets which describe the entities’ physical characteristics, and b) agents which describe their behaviour according to their goal and previous learning experiences. This approach diverges from the traditional approach where both aspects are often conflated. It has many advantages in terms of reusability of one or the other aspect for different purposes as well as composability when building simulations. For example, the way an asset is used on a network can greatly vary while its physical characteristics are the same – this is the case for two identical battery systems which usage will vary depending on the purpose of their installation. While any battery can be described by its physical properties (e.g. capacity, lifetime, and depth of discharge), its behaviour will vary depending on who is using it and what their aim is. The model is populated using data describing both aspects (physical characteristics and behaviour) and can be updated as required depending on what simulation is to be run. For example, data can be used to describe the environment to which the agents respond to – e.g. weather for solar panels, or to describe the assets and their relation to one another – e.g. the network assets. Finally, when running a simulation, MODAM calls on its module manager that coordinates the different plugins, automates the creation of the assets and agents using factories, and schedules their execution which can be done sequentially or in parallel for faster execution. Building agent-based models in this way has proven fast when adding new complex behaviours, as well as new types of assets. Simulations have been run to understand the potential impact of changes on the network in terms of assets (e.g. installation of decentralised generators) or behaviours (e.g. response to different management aims). While this platform has been developed within the context of a project focussing on the electricity domain, the core of the software, MODAM, can be extended to other domains such as transport which is part of future work with the addition of electric vehicles.

A probabilistic framework to monitor a multi-mode outdoor robot

This paper presents an approach to autonomously monitor the behavior of a robot endowed with several navigation and locomotion modes, adapted to the terrain to traverse. The mode selection process is done in two steps: the best suited mode is firstly selected on the basis of initial information or a qualitative map built on-line by the robot. Then, the motions of the robot are monitored by various processes that update mode transition probabilities in a Markov system. The paper focuses on this latter selection process: the overall approach is depicted, and preliminary experimental results are presented

The emergence of Leptospira borgpetersenii serovar Arborea as the dominant infecting serovar following the summer of natural disasters in Queensland, Australia 2011

The following research reports the emergence of Leptospira borgpetersenii serovar Arborea as the dominant infecting serovar following the summer of disasters and the ensuing clean up in Queensland, Australia during 2011. For the 12 month period (1 January to 31 December) L. borgpetersenii serovar Arborea accounted for over 49% of infections. In response to a flooding event public health officials need to issue community wide announcements warning the population about the dangers of leptospirosis and other water borne diseases. Communication with physicians working in the affected community should also be increased to update physicians with information such as clinical presentation of leptospirosis and other waterborne diseases. These recommendations will furnish public health officials with considerations for disease management when dealing with future disaster management programs.

Tracking-based moving object detection

We present a novel approach for multi-object detection in aerial videos based on tracking. The proposed method mainly involves three steps. Firstly, the spatial-temporal saliency is employed to detect moving objects. Secondly, the detected objects are tracked by mean shift in the subsequent frames. Finally, the saliency results are fused with the weight map generated by tracking to get refined detection results, and in turn the modified detection results are used to update the tracking models. The proposed algorithm is evaluated on VIVID aerial videos, and the results show that our approach can reliably detect moving objects even in challenging situations. Meanwhile, the proposed method can process videos in real time, without the effect of time delay.

Online self-supervised multi-instance segmentation of dynamic objects

This paper presents a method for the continuous segmentation of dynamic objects using only a vehicle mounted monocular camera without any prior knowledge of the object’s appearance. Prior work in online static/dynamic segmentation is extended to identify multiple instances of dynamic objects by introducing an unsupervised motion clustering step. These clusters are then used to update a multi-class classifier within a self-supervised framework. In contrast to many tracking-by-detection based methods, our system is able to detect dynamic objects without any prior knowledge of their visual appearance shape or location. Furthermore, the classifier is used to propagate labels of the same object in previous frames, which facilitates the continuous tracking of individual objects based on motion. The proposed system is evaluated using recall and false alarm metrics in addition to a new multi-instance labelled dataset to evaluate the performance of segmenting multiple instances of objects.

New technologies for assessing the contact lens wearing eye

New technologies for examination of the anterior eye in contact lens practice don’t appear to have taken a huge leap in the past decade however there a several novel adaptations of existing technology worthy of note. In other areas of health we have self-diagnosis via smartphone or other gadgets adapted as medical devices. In practice and research in vitro and in vivo new adaptive technologies have expanded our capabilities in assessing the anterior eye, in particular corneal and conjunctival confocal microscopy.

Factor Five : Transforming the Global Economy through 80% Improvements in Resource Productivity

The 21st century will see monumental change. Either the human race will use its knowledge and skills and change the way it interacts with the environment, or the environment will change the way it interacts with its inhabitants. In the first case, the focus of this book, we would see our sophisticated understanding in areas such as physics, chemistry, engineering, biology, planning, commerce, business and governance accumulated over the last 1,000 years brought to bear on the challenge of dramatically reducing our pressure on the environment. The second case however is the opposite scenario, involving the decline of the planet’s ecosystems until they reach thresholds where recovery is not possible, and following which we have no idea what happens. For instance, if we fail to respond to Sir Nicolas Stern’s call to meet appropriate stabilisation trajectories for greenhouse gas emissions, and we allow the average temperature of our planets surface to increase by 4-6 degrees Celsius, we will see staggering changes to our environment, including rapidly rising sea level, withering crops, diminishing water reserves, drought, cyclones, floods… allowing this to happen will be the failure of our species, and those that survive will have a deadly legacy. In this update to the 1997 International Best Seller, Factor Four, Ernst von Weizsäcker again leads a team to present a compelling case for sector wide advances that can deliver significant resource productivity improvements over the coming century. The purpose of this book is to inspire hope and to then inform meaningful action in the coming decades to respond to the greatest challenge our species has ever faced – that of living in harmony with our planet and its other inhabitants.

A new dynamic accumulator for batch updates

A dynamic accumulator is an algorithm, which gathers together a large set of elements into a constant-size value such that for a given element accumulated, there is a witness confirming that the element was indeed included into the value, with a property that accumulated elements can be dynamically added and deleted into/from the original set such that the cost of an addition or deletion operation is independent of the number of accumulated elements. Although the first accumulator was presented ten years ago, there is still no standard formal definition of accumulators. In this paper, we generalize formal definitions for accumulators, formulate a security game for dynamic accumulators so-called Chosen Element Attack (CEA), and propose a new dynamic accumulator for batch updates based on the Paillier cryptosystem. Our construction makes a batch of update operations at unit cost. We prove its security under the extended strong RSA (es-RSA) assumption

Fast re-parameterisation of Gaussian mixture models for robotics applications

Autonomous navigation and picture compilation tasks require robust feature descriptions or models. Given the non Gaussian nature of sensor observations, it will be shown that Gaussian mixture models provide a general probabilistic representation allowing analytical solutions to the update and prediction operations in the general Bayesian filtering problem. Each operation in the Bayesian filter for Gaussian mixture models multiplicatively increases the number of parameters in the representation leading to the need for a re-parameterisation step. A computationally efficient re-parameterisation step will be demonstrated resulting in a compact and accurate estimate of the true distribution.

Editorial : Law and ethics for the bioeconomy and beyond

The convergence of biological, technological and economic realms of life has fostered the development of the bioeconomy as a new feature of contemporary society. As the meaning of life and the human body is redefined in the context of the bioeconomy, new challenges have emerged for ethics and law In the face of these challenges, it is imperative that the currency of regulatory frameworks is maintained through the processes of regular review and update. The National Health and Medical Research Council has recently released the new National Statement on Ethical Conduct in Human Research to provide guidance for health research in Australia. The new National Statement will play an important part in supporting innovation and the development of the knowledge economy.

A multi-hierarchical motorway ramp signalling strategy

Ramp signalling is an access control for motorways, in which a traffic signal is placed at on-ramps to regulate the rate of vehicles entering the motorway and thus to preserve the motorway capacity. In general, ramp signalling algorithms fall into two categories: local control and coordinated control by their effective scope. Coordinated ramp signalling strategies make use of measurements from the entire motorway network to operate individual ramp signals for the optimal performances at the network level. This study proposes a multi-hierarchical strategy for coordinated ramp signalling. The strategy is structured in two layers. At the higher layer with a longer update interval, coordination group is assembled and disassembled based on the location of high-risk breakdown flow. At the lower layer with a shorter update interval, individual ramps are hired to serve the coordination and are also released based on the prevailing congestion level on the ramp. This strategy is modelled and applied to the northbound Pacific Motorway micro-simulation platform (AIMSUN). The simulation results show an effective congestion mitigation of the proposed strategy.