The implementation of a novel, bio-inspired, robotic security system

The implementation of a robotic security solution generally requires one algorithm to route the robot around the environment and another algorithm to perform anomaly detection. Solutions to the routing problem require the robot to have a good estimate of its own pose. We present a novel security system that uses metrics generated by the localisation algorithm to perform adaptive anomaly detection. The localisation algorithm is a vision-based SLAM solution called RatSLAM, based on mechanisms within the hippocampus. The anomaly detection algorithm is based on the mechanisms used by the immune system to identify threats to the body. The system is explored using data gathered within an unmodified office environment. It is shown that the algorithm successfully reacts to the presence of people and objects in areas where they are not usually present and is tolerised against the presence of people in environments that are usually dynamic.

Building research capacity in the nursing workforce : the design and evaluation of the nurse researcher role

Objectives: The Nurse Researcher Project (NRP) was initiated to support development of a nursing research and evidence based practice culture in Cancer Care Services (CCS) in a large tertiary hospital in Australia. The position was established and evaluated to inform future directions in the organisation.---------- Background: The demand for quality cancer care has been expanding over the past decades. Nurses are well placed to make an impact on improving health outcomes of people affected by cancer. At the same time, there is a robust body of literature documenting the barriers to undertaking and utilising research by and for nurses and nursing. A number of strategies have been implemented to address these barriers including a range of staff researcher positions but there is scant attention to evaluating the outcomes of these strategies. The role of nurse researcher has been documented in the literature with the aim to provide support to nurses in the clinical setting. There is, to date, little information in relation to the design, implementation and evaluation of this role.---------- Design: The Donabedian’s model of program evaluation was used to implement and evaluate this initiative.---------- Methods: The ‘NRP’ outlined the steps needed to implement the nurse researcher role in a clinical setting. The steps involved the design of the role, planning for the support system for the role, and evaluation of outcomes of the role over two years.---------- Discussion: This paper proposes an innovative and feasible model to support clinical nursing research which would be relevant to a range of service areas.---------- Conclusion: Nurse researchers are able to play a crucial role in advancing nursing knowledge and facilitating evidence based practice, especially when placed to support a specialised team of nurses at a service level. This role can be implemented through appropriate planning of the position, building a support system and incorporating an evaluation plan.

Effects of lead exposure on hippocampal metabotropic glutamate receptor subtype 3 and 7 in developmental rats

Background A complete explanation of the mechanisms by which Pb2+ exerts toxic effects on developmental central nervous system remains unknown. Glutamate is critical to the developing brain through various subtypes of ionotropic or metabotropic glutamate receptors (mGluRs). Ionotropic N-methyl-D-aspartate receptors have been considered as a principal target in lead-induced neurotoxicity. The relationship between mGluR3/mGluR7 and synaptic plasticity had been verified by many recent studies. The present study aimed to examine the role of mGluR3/mGluR7 in lead-induced neurotoxicity. Methods Twenty-four adult and female rats were randomly selected and placed on control or 0.2% lead acetate during gestation and lactation. Blood lead and hippocampal lead levels of pups were analyzed at weaning to evaluate the actual lead content at the end of the exposure. Impairments of short -term memory and long-term memory of pups were assessed by tests using Morris water maze and by detection of hippocampal ultrastructural alterations on electron microscopy. The impact of lead exposure on mGluR3 and mGluR7 mRNA expression in hippocampal tissue of pups were investigated by quantitative real-time polymerase chain reaction and its potential role in lead neurotoxicity were discussed. Results Lead levels of blood and hippocampi in the lead-exposed rats were significantly higher than those in the controls (P < 0.001). In tests using Morris Water Maze, the overall decrease in goal latency and swimming distance was taken to indicate that controls had shorter latencies and distance than lead-exposed rats (P = 0.001 and P < 0.001 by repeated-measures analysis of variance). On transmission electron microscopy neuronal ultrastructural alterations were observed and the results of real-time polymerase chain reaction showed that exposure to 0.2% lead acetate did not substantially change gene expression of mGluR3 and mGluR7 mRNA compared with controls. Conclusion Exposure to lead before and after birth can damage short-term and long-term memory ability of young rats and hippocampal ultrastructure. However, the current study does not provide evidence that the expression of rat hippocampal mGluR3 and mGluR7 can be altered by systemic administration of lead during gestation and lactation, which are informative for the field of lead-induced developmental neurotoxicity noting that it seems not to be worthwhile to include mGluR3 and mGluR7 in future studies. Background

Dengue fever and el nino-southern oscillation in Queensland, Australia : a time series predictive model

Background It remains unclear over whether it is possible to develop an epidemic forecasting model for transmission of dengue fever in Queensland, Australia. Objectives To examine the potential impact of El Niño/Southern Oscillation on the transmission of dengue fever in Queensland, Australia and explore the possibility of developing a forecast model of dengue fever. Methods Data on the Southern Oscillation Index (SOI), an indicator of El Niño/Southern Oscillation activity, were obtained from the Australian Bureau of Meteorology. Numbers of dengue fever cases notified and the numbers of postcode areas with dengue fever cases between January 1993 and December 2005 were obtained from the Queensland Health and relevant population data were obtained from the Australia Bureau of Statistics. A multivariate Seasonal Auto-regressive Integrated Moving Average model was developed and validated by dividing the data file into two datasets: the data from January 1993 to December 2003 were used to construct a model and those from January 2004 to December 2005 were used to validate it. Results A decrease in the average SOI (ie, warmer conditions) during the preceding 3–12 months was significantly associated with an increase in the monthly numbers of postcode areas with dengue fever cases (β=−0.038; p = 0.019). Predicted values from the Seasonal Auto-regressive Integrated Moving Average model were consistent with the observed values in the validation dataset (root-mean-square percentage error: 1.93%). Conclusions Climate variability is directly and/or indirectly associated with dengue transmission and the development of an SOI-based epidemic forecasting system is possible for dengue fever in Queensland, Australia.

Electronic telephone directory listings : preferred sampling frame for a population-based study of childhood cancer in Australia

PURPOSE: We report our telephone-based system for selecting community control series appropriate for a complete Australia-wide series of Ewing's sarcoma cases. METHODS: We used electronic directory random sampling to select age-matched controls. The sampling has all listed telephone numbers on an up-dated CD-Rom. RESULTS: 95% of 2245 telephone numbers selected were successfully contacted. The mean number of attempts needed was 1.94, 58% answering at the first attempt. On average, we needed 4.5 contacts per control selected. Calls were more likely to be successful (reach a respondent) when made in the evening (except Saturdays). The overall response rate among contacted telephone numbers was 92.8%. Participation rates among female and male respondents were practically the same. The exclusion of unlisted numbers (13.5% of connected households) and unconnected households (3.7%) led to potential selection bias. However, restricting the case series to listed cases only, plus having external information on the direction of potential bias allow meaningful interpretation of our data. CONCLUSION: Sampling from an electronic directory is convenient, economical and simple, and gives a very good yield of eligible subjects compared to other methods.

Space-frequency block code with matched rotation for MIMO-OFDM system with limited feedback

This paper presents a novel matched rotation precoding (MRP) scheme to design a rate one space-frequency block code (SFBC) and a multirate SFBC for MIMO-OFDM systems with limited feedback. The proposed rate one MRP and multirate MRP can always achieve full transmit diversity and optimal system performance for arbitrary number of antennas, subcarrier intervals, and subcarrier groupings, with limited channel knowledge required by the transmit antennas. The optimization process of the rate one MRP is simple and easily visualized so that the optimal rotation angle can be derived explicitly, or even intuitively for some cases. The multirate MRP has a complex optimization process, but it has a better spectral efficiency and provides a relatively smooth balance between system performance and transmission rate. Simulations show that the proposed SFBC with MRP can overcome the diversity loss for specific propagation scenarios, always improve the system performance, and demonstrate flexible performance with large performance gain. Therefore the proposed SFBCs with MRP demonstrate flexibility and feasibility so that it is more suitable for a practical MIMO-OFDM system with dynamic parameters.

Optimal allocation and sizing of DGs in a distribution system using PSO

In this paper, the optimal allocation and sizing of distributed generators (DGs) in a distribution system is studied. To achieve this goal, an optimization problem should be solved in which the main objective is to minimize the DGs cost and to maximise the reliability simultaneously. The active power balance between loads and DGs during the isolation time is used as a constraint. Another point considered in this process is the load shedding. It means that if the summation of DGs active power in a zone, isolated by the sectionalizers because of a fault, is less than the total active power of loads located in that zone, the program start shedding the loads in one-by-one using the priority rule still the active power balance is satisfied. This assumption decreases the reliability index, SAIDI, compared with the case loads in a zone are shed when total DGs power is less than the total load power. To validate the proposed method, a 17-bus distribution system is employed and the results are analysed.

Building climate change resilience and adaptive capacity in Australia’s community sector using social media and technology innovation

Public and private sector organisations worldwide are putting strategies in place to manage the commercial and operational risks of climate change. However, community organisations are lagging behind in their understanding and preparedness, despite them being among the most exposed to the effects of climate change impacts and regulation. This poster presents a proposal for a multidisciplinary study that addresses this issue by developing, testing and applying a novel climate risk assessment methodology that is tailored to the needs of Australia’s community sector and its clients. Strategies to mitigate risks and build resilience and adaptive capacity will be identified including new opportunities afforded by urban informatics, social media, and technologies of scale making.

Driving performance on monotonous roads

Driving on motorways has largely been reduced to a lane-keeping task with cruise control. Rapidly, drivers are likely to get bored with such a task and take their attention away from the road. This is of concern in terms of road safety – particularly for professional drivers - since inattention has been identified as one of the main contributing factors to road crashes and is estimated to be involved in 20 to 30% of these crashes. Furthermore, drivers are not aware that their vigilance level has decreased and that their driving performance is impaired. Intelligent Transportation System (ITS) intervention can be used as a countermeasure against vigilance decrement. This paper aims to identify a variety of metrics impacted during monotonous driving - ranging from vehicle data to physiological variables - and relate them to two monotonous factors namely the monotony of the road design (straightness) and the monotony of the environment (landscape, signage, traffic). Data are collected in a driving simulator instrumented with an eye tracking system, a heart rate monitor and an electrodermal activity device (N=25 participants). The two monotonous factors are varied (high and low) leading to the use of four different driving scenarios (40 minutes each). We show with Generalised Linear Mixed Models that driver performance decreases faster when the road is monotonous. We also highlight that road monotony impairs a variety of driving performance and vigilance measures, ranging from speed, lateral position of the vehicle to physiological measurements such as heart rate variability, blink frequency and electrodermal activity. This study informs road designers of the importance of having a varied road environment. It also provides a range of metrics that can be used to detect in real-time the impairment of driving performance on monotonous roads. Such knowledge could result in the development of an in-vehicle device warning drivers at early signs of driving performance impairment on monotonous roads.

Alternate structural system of incorporating flat bed rail wagons as low volume road bridge decks

The stimulus for this project rose from the need to find an alternative solution to aging superstructures of road-bridge in low volume roads (LVR). The solution investigated, designed and consequently plans to construct, involved replacing an aging super-structure of a 10m span bridge with Flat-Bed Rail Wagon (FBRW). The main focus of this paper is to present alternate structural system for the design of the FBRW as road bridge deck conforming to AS5100. The structural adequacy of the primary members of the FBRW was first validated using full scale experimental investigation to AS5100 serviceability and ultimate limit state loading. The bare FBRW was further developed to include a running surface. Two options were evaluated during the design phase, namely timber and reinforced concrete. First option, which is presented here, involved strengthening of the FBRW using numerous steel sections and overlaying the bridge deck with timber planks. The idea of this approach was to use all the primary and secondary members of the FBRW in load sharing and to provide additional members where weaknesses in the original members arose. The second option, which was the preferred option for construction, involved use of primary members only with an overlaying reinforced concrete slab deck. This option minimised the risk associated with any uncertainty of secondary members to its structural adequacy. The paper will report selected results of the experiment as well as the design phases of option one with conclusions highlighting the viability of option 1 and its limitations.

UAS mission path planning system (MPPS) using hybrid-game coupled to multi-objective optimiser

This paper presents the application of advanced optimization techniques to unmanned aerial system mission path planning system (MPPS) using multi-objective evolutionary algorithms (MOEAs). Two types of multi-objective optimizers are compared; the MOEA nondominated sorting genetic algorithm II and a hybrid-game strategy are implemented to produce a set of optimal collision-free trajectories in a three-dimensional environment. The resulting trajectories on a three-dimensional terrain are collision-free and are represented by using Bézier spline curves from start position to target and then target to start position or different positions with altitude constraints. The efficiency of the two optimization methods is compared in terms of computational cost and design quality. Numerical results show the benefits of adding a hybrid-game strategy to a MOEA and for a MPPS.

Optimal mission path planning (MPP) for an air sampling unmanned aerial system

This paper presents advanced optimization techniques for Mission Path Planning (MPP) of a UAS fitted with a spore trap to detect and monitor spores and plant pathogens. The UAV MPP aims to optimise the mission path planning search and monitoring of spores and plant pathogens that may allow the agricultural sector to be more competitive and more reliable. The UAV will be fitted with an air sampling or spore trap to detect and monitor spores and plant pathogens in remote areas not accessible to current stationary monitor methods. The optimal paths are computed using a Multi-Objective Evolutionary Algorithms (MOEAs). Two types of multi-objective optimisers are compared; the MOEA Non-dominated Sorting Genetic Algorithms II (NSGA-II) and Hybrid Game are implemented to produce a set of optimal collision-free trajectories in three-dimensional environment. The trajectories on a three-dimension terrain, which are generated off-line, are collision-free and are represented by using Bézier spline curves from start position to target and then target to start position or different position with altitude constraints. The efficiency of the two optimization methods is compared in terms of computational cost and design quality. Numerical results show the benefits of coupling a Hybrid-Game strategy to a MOEA for MPP tasks. The reduction of numerical cost is an important point as the faster the algorithm converges the better the algorithms is for an off-line design and for future on-line decisions of the UAV.

Design optimisation using advanced artificial intelligent system coupled to hybrid-game strategies

One of the main aims in artificial intelligent system is to develop robust and efficient optimisation methods for Multi-Objective (MO) and Multidisciplinary Design (MDO) design problems. The paper investigates two different optimisation techniques for multi-objective design optimisation problems. The first optimisation method is a Non-Dominated Sorting Genetic Algorithm II (NSGA-II). The second method combines the concepts of Nash-equilibrium and Pareto optimality with Multi-Objective Evolutionary Algorithms (MOEAs) which is denoted as Hybrid-Game. Numerical results from the two approaches are compared in terms of the quality of model and computational expense. The benefit of using the distributed hybrid game methodology for multi-objective design problems is demonstrated.

Comprehensive evaluation of driver gaze pattern using fuzzy rules for driver training

The over representation of novice drivers in crashes is alarming. Research indicates that one in five drivers’ crashes within their first year of driving. Driver training is one of the interventions aimed at decreasing the number of crashes that involve young drivers. Currently, there is a need to develop comprehensive driver evaluation system that benefits from the advances in Driver Assistance Systems. Since driving is dependent on fuzzy inputs from the driver (i.e. approximate distance calculation from the other vehicles, approximate assumption of the other vehicle speed), it is necessary that the evaluation system is based on criteria and rules that handles uncertain and fuzzy characteristics of the drive. This paper presents a system that evaluates the data stream acquired from multiple in-vehicle sensors (acquired from Driver Vehicle Environment-DVE) using fuzzy rules and classifies the driving manoeuvres (i.e. overtake, lane change and turn) as low risk or high risk. The fuzzy rules use parameters such as following distance, frequency of mirror checks, gaze depth and scan area, distance with respect to lanes and excessive acceleration or braking during the manoeuvre to assess risk. The fuzzy rules to estimate risk are designed after analysing the selected driving manoeuvres performed by driver trainers. This paper focuses mainly on the difference in gaze pattern for experienced and novice drivers during the selected manoeuvres. Using this system, trainers of novice drivers would be able to empirically evaluate and give feedback to the novice drivers regarding their driving behaviour.

Generation next : post-cinema Australian moviemaking, innovation and implications for cultural policy

The Australian screen industries are a leading domestic creative industry sector at a crossroad. New production, distribution and exhibition technologies are challenging traditional models of ‘filmmaking’. For the screen industries to remain competitive they must renovate business models for an emerging marketplace. This paper is a preliminary examination of three key aspects of next generation filmmaking: post-cinema approaches to screen production, emerging production and business models, and issues for policy.