Exploring the properties of macroscopic fundamental diagram : analysing Brisbane urban network

This thesis explored traffic characteristics at the aggregate level for area-wide traffic monitoring of large urban area. It focused on three aspects: understanding a macroscopic network performance under real-time traffic information provision, measuring traffic performance of a signalised arterial network using available data sets, and discussing network zoning for monitoring purposes in the case of Brisbane, Australia. This work presented the use of probe vehicle data for estimating traffic state variables, and illustrated dynamic features of regional traffic performance of Brisbane. The results confirmed the viability and effectiveness of area-wide traffic monitoring.

Victorian Public Libraries: Our Future, Our Skills. Research Report

This research study represents a key part of the program of Statewide Public Library Development Projects delivered by the State Library of Victoria between 2011 and 2014 in partnership with Public Libraries Victoria Network (PLVN), the peak body for Victoria’s 47 public library services. The overarching objectives of this project were: - to develop a framework to articulate the core competencies required by the public library workforce for the 21st century - to conduct a skills audit of Victorian public library staff in order to collect evidence of the current skills and to anticipate future skills requirements - to deliver a report that analyses the audit findings and makes recommendations on training needs and strategies to prepare for the future delivery of public library services in Victoria. The study built on the 2008 report Workforce sustainability and leadership: Survey, analysis and planning, developed for the State Library of Victoria and PLVN, in which three types of workplace skills were delineated: cognitive (or Foundation), technical (or Professional) and Behavioural skills. Following industry discussion and review, a framework comprising 59 skill-sets within the three distinct skills areas was finalised in October 2013. The skills audit, which comprised an Individual survey and a Management survey with questionnaires directly based on the skills framework, was undertaken between late November and December 2013. This report presents the analysis and interpretation of the data collected through the two surveys.

Component modeling for SCADA network mapping

Supervisory Control and Data Acquisition systems (SCADA) are widely used to control critical infrastructure automatically. Capturing and analyzing packet-level traffic flowing through such a network is an essential requirement for problems such as legacy network mapping and fault detection. Within the framework of captured network traffic, we present a simple modeling technique, which supports the mapping of the SCADA network topology via traffic monitoring. By characterizing atomic network components in terms of their input-output topology and the relationship between their data traffic logs, we show that these modeling primitives have good compositional behaviour, which allows complex networks to be modeled. Finally, the predictions generated by our model are found to be in good agreement with experimentally obtained traffic.

Identification of pre-spike network in patients with mesial temporal lobe epilepsy

Background: Seizures and interictal spikes in mesial temporal lobe epilepsy (MTLE) affect a network of brain regions rather than a single epileptic focus. Simultaneous electroencephalography and functional magnetic resonance imaging (EEG-fMRI) studies have demonstrated a functional network in which hemodynamic changes are time-locked to spikes. However, whether this reflects the propagation of neuronal activity from a focus, or conversely the activation of a network linked to spike generation remains unknown. The functional connectivity (FC) changes prior to spikes may provide information about the connectivity changes that lead to the generation of spikes. We used EEG-fMRI to investigate FC changes immediately prior to the appearance of interictal spikes on EEG in patients with MTLE. Methods/principal findings: Fifteen patients with MTLE underwent continuous EEG-fMRI during rest. Spikes were identified on EEG and three 10 s epochs were defined relative to spike onset: spike (0–10 s), pre-spike (−10 to 0 s), and rest (−20 to −10 s, with no previous spikes in the preceding 45s). Significant spike-related activation in the hippocampus ipsilateral to the seizure focus was found compared to the pre-spike and rest epochs. The peak voxel within the hippocampus ipsilateral to the seizure focus was used as a seed region for FC analysis in the three conditions. A significant change in FC patterns was observed before the appearance of electrographic spikes. Specifically, there was significant loss of coherence between both hippocampi during the pre-spike period compared to spike and rest states. Conclusion/significance: In keeping with previous findings of abnormal inter-hemispheric hippocampal connectivity in MTLE, our findings specifically link reduced connectivity to the period immediately before spikes. This brief decoupling is consistent with a deficit in mutual (inter-hemispheric) hippocampal inhibition that may predispose to spike generation.

The role of university research centres in building road safety capacity : implications for China

In recent decades, highly motorised countries, such as Australia, have witnessed significant improvements in population health through reductions in fatalities and injuries from road traffic crashes. In Australia, concerted efforts have been made to reduce the road trauma burden since road fatalities reached their highest level in in the early 1970s. Since that time, many improvements have been made drawing on various disciplines to reduce the trauma burden (e.g., road and vehicle design, road user education, traffic law enforcement practices and enforcement technologies). While road fatalities have declined significantly since the mid-1970s, road trauma remains a serious public health concern in Australia. China has recently become the largest car market in the world (Ma, Li, Zhou, Duan, & Bishai, 2012). This rapid motorisation has been accompanied by substantial expansion of the road network as well as a large road trauma burden. Road traffic injuries are a major cause of death in China, reported as accounting for one third of all injury-deaths between 2002 and 2006 (Ma et al., 2012). In common with Australia, China has experienced a reported decline in fatalities since 2002 (see Hu, Wen & Baker, 2008). However, there remains a strong need for action in this area as rates of motorisation continue to climb in China. In Australia, a wide range of organisations have contributed to the improvements in road safety including government agencies, professional organisations, advocacy groups and research centres. In particular, Australia has several highly regarded and multi-disciplinary, university-based research centres that work across a range of road safety fields, including engineering, intelligent transportation systems, the psychology of road user behaviour, and traffic law enforcement. Besides conducting high-quality research, these centres fulfil an important advocacy role in promoting safer road use and facilitating collaborations with government and other agencies, at both the national and international level. To illustrate the role of these centres, an overview will be provided of the Centre for Accident Research and Road Safety-Queensland (CARRS-Q), which was established in 1996 and has gone on to become a recognised world-leader in road safety and injury prevention research. The Centre’s research findings are used to provide evidence-based recommendations to government and have directly contributed to promoting safer road use in Australia. Since 2006, CARRS-Q has also developed strong collaborative links with various universities and organisations in China to assist in building understanding, connections and capacity to assist in reducing the road trauma burden. References Hu, G., Wen, M., Baker, T. D., & Baker, S. P. (2008). Road-traffic deaths in China, 1985–2005: threat and opportunity. Injury Prevention, 14, 149-153. Ma, S., Li, Q., Zhou, M., Duan, L., & Bishai, D. (2012). Road Traffic Injury in China: A Review of National Data Sources. Traffic Injury Prevention, 13(S1), 57-63.

A Hybrid Queue-based Bayesian Network framework for passenger facilitation modelling

This paper presents a novel framework for the modelling of passenger facilitation in a complex environment. The research is motivated by the challenges in the airport complex system, where there are multiple stakeholders, differing operational objectives and complex interactions and interdependencies between different parts of the airport system. Traditional methods for airport terminal modelling do not explicitly address the need for understanding causal relationships in a dynamic environment. Additionally, existing Bayesian Network (BN) models, which provide a means for capturing causal relationships, only present a static snapshot of a system. A method to integrate a BN complex systems model with stochastic queuing theory is developed based on the properties of the Poisson and exponential distributions. The resultant Hybrid Queue-based Bayesian Network (HQBN) framework enables the simulation of arbitrary factors, their relationships, and their effects on passenger flow and vice versa. A case study implementation of the framework is demonstrated on the inbound passenger facilitation process at Brisbane International Airport. The predicted outputs of the model, in terms of cumulative passenger flow at intermediary and end points in the inbound process, are found to have an R2 goodness of fit of 0.9994 and 0.9982 respectively over a 10 h test period. The utility of the framework is demonstrated on a number of usage scenarios including causal analysis and ‘what-if’ analysis. This framework provides the ability to analyse and simulate a dynamic complex system, and can be applied to other socio-technical systems such as hospitals.

‘Ngulluck Katitj Wah Koorl Koorliny/ Us mob going along learning to research together’ : drawing on action research to develop a literature review on Indigenous gendered health and wellbeing

This paper describes the collaborative work practices of the Health and Wellbeing Node within the National Indigenous Research and Knowledges Network (NIRAKN). The authors reflect on the processes they used to research and develop a literature review. As a newly established research team, the Health and Wellbeing Node members developed a collaborative approach that was informed by Action Research practices and underpinned by Indigenous ways of working. The authors identify strong links between Action Research and Indigenous processes. They suggest that, through ongoing cycles of research and review, the NIRAKN Health and Wellbeing Node developed a culturally safe, respectful and trulycollaborative way of working together and forming the identity of their work group. In this paper, they describe their developing work processes and explain the way that pictorial conceptual models contributed to their emerging ideas.

Development and integration of a solar powered unmanned aerial vehicle and a wireless sensor network to monitor greenhouse gases

Measuring gases for environmental monitoring is a demanding task that requires long periods of observation and large numbers of sensors. Wireless Sensor Networks (WSNs) and Unmanned Aerial Vehicles (UAVs) currently represent the best alternative to monitor large, remote, and difficult access areas, as these technologies have the possibility of carrying specialized gas sensing systems. This paper presents the development and integration of a WSN and an UAV powered by solar energy in order to enhance their functionality and broader their applications. A gas sensing system implementing nanostructured metal oxide (MOX) and non-dispersive infrared sensors was developed to measure concentrations of CH4 and CO2. Laboratory, bench and field testing results demonstrate the capability of UAV to capture, analyze and geo-locate a gas sample during flight operations. The field testing integrated ground sensor nodes and the UAV to measure CO2 concentration at ground and low aerial altitudes, simultaneously. Data collected during the mission was transmitted in real time to a central node for analysis and 3D mapping of the target gas. The results highlights the accomplishment of the first flight mission of a solar powered UAV equipped with a CO2 sensing system integrated with a WSN. The system provides an effective 3D monitoring and can be used in a wide range of environmental applications such as agriculture, bushfires, mining studies, zoology and botanical studies using a ubiquitous low cost technology.

DS-VBF : dual sink vector-based routing protocol for underwater wireless sensor network

Underwater wireless sensor networks (UWSNs) have become the seat of researchers' attention recently due to their proficiency to explore underwater areas and design different applications for marine discovery and oceanic surveillance. One of the main objectives of each deployed underwater network is discovering the optimized path over sensor nodes to transmit the monitored data to onshore station. The process of transmitting data consumes energy of each node, while energy is limited in UWSNs. So energy efficiency is a challenge in underwater wireless sensor network. Dual sinks vector based forwarding (DS-VBF) takes both residual energy and location information into consideration as priority factors to discover an optimized routing path to save energy in underwater networks. The modified routing protocol employs dual sinks on the water surface which improves network lifetime. According to deployment of dual sinks, packet delivery ratio and the average end to end delay are enhanced. Based on our simulation results in comparison with VBF, average end to end delay reduced more than 80%, remaining energy increased 10%, and the increment of packet reception ratio was about 70%.

A parallel approach to social network generation and agent-based epidemic simulation

Understanding the dynamics of disease spread is essential in contexts such as estimating load on medical services, as well as risk assessment and interven- tion policies against large-scale epidemic outbreaks. However, most of the information is available after the outbreak itself, and preemptive assessment is far from trivial. Here, we report on an agent-based model developed to investigate such epidemic events in a stylised urban environment. For most diseases, infection of a new individual may occur from casual contact in crowds as well as from repeated interactions with social partners such as work colleagues or family members. Our model therefore accounts for these two phenomena. Given the scale of the system, efficient parallel computing is required. In this presentation, we focus on aspects related to paralllelisation for large networks generation and massively multi-agent simulations.

Prediction of GMA welding characteristic parameter by artificial neural network system

Nowadays, demand for automated Gas metal arc welding (GMAW) is growing and consequently need for intelligent systems is increased to ensure the accuracy of the procedure. To date, welding pool geometry has been the most used factor in quality assessment of intelligent welding systems. But, it has recently been found that Mahalanobis Distance (MD) not only can be used for this purpose but also is more efficient. In the present paper, Artificial Neural Networks (ANN) has been used for prediction of MD parameter. However, advantages and disadvantages of other methods have been discussed. The Levenberg–Marquardt algorithm was found to be the most effective algorithm for GMAW process. It is known that the number of neurons plays an important role in optimal network design. In this work, using trial and error method, it has been found that 30 is the optimal number of neurons. The model has been investigated with different number of layers in Multilayer Perceptron (MLP) architecture and has been shown that for the aim of this work the optimal result is obtained when using MLP with one layer. Robustness of the system has been evaluated by adding noise into the input data and studying the effect of the noise in prediction capability of the network. The experiments for this study were conducted in an automated GMAW setup that was integrated with data acquisition system and prepared in a laboratory for welding of steel plate with 12 mm in thickness. The accuracy of the network was evaluated by Root Mean Squared (RMS) error between the measured and the estimated values. The low error value (about 0.008) reflects the good accuracy of the model. Also the comparison of the predicted results by ANN and the test data set showed very good agreement that reveals the predictive power of the model. Therefore, the ANN model offered in here for GMA welding process can be used effectively for prediction goals.

Retrieving trip information from a discrete detectors network : The case of Brisbane Bluetooth detectors

Automatic Vehicle Identification Systems are being increasingly used as a new source of travel information. As in the last decades these systems relied on expensive new technologies, few of them were scattered along a networks making thus Travel-Time and Average Speed estimation their main objectives. However, as their price dropped, the opportunity of building dense AVI networks arose, as in Brisbane where more than 250 Bluetooth detectors are now installed. As a consequence this technology represents an effective means to acquire accurate time dependant Origin Destination information. In order to obtain reliable estimations, however, a number of issues need to be addressed. Some of these problems stem from the structure of a network made out of isolated detectors itself while others are inherent of Bluetooth technology (overlapping detection area, missing detections,\...). The aim of this paper is threefold: First, after having presented the level of details that can be reached with a network of isolated detectors we present how we modelled Brisbane's network, keeping only the information valuable for the retrieval of trip information. Second, we give an overview of the issues inherent to the Bluetooth technology and we propose a method for retrieving the itineraries of the individual Bluetooth vehicles. Last, through a comparison with Brisbane Transport Strategic Model results, we highlight the opportunities and the limits of Bluetooth detectors networks. The aim of this paper is twofold. We first give a comprehensive overview of the aforementioned issues. Further, we propose a methodology that can be followed, in order to cleanse, correct and aggregate Bluetooth data. We postulate that the methods introduced by this paper are the first crucial steps that need to be followed in order to compute accurate Origin-Destination matrices in urban road networks.

Application of a Bayesian Network complex system model to a successful community electricity demand reduction program

Utilities worldwide are focused on supplying peak electricity demand reliably and cost effectively, requiring a thorough understanding of all the factors influencing residential electricity use at peak times. An electricity demand reduction project based on comprehensive residential consumer engagement was established within an Australian community in 2008, and by 2011, peak demand had decreased to below pre-intervention levels. This paper applied field data discovered through qualitative in-depth interviews of 22 residential households at the community to a Bayesian Network complex system model to examine whether the system model could explain successful peak demand reduction in the case study location. The knowledge and understanding acquired through insights into the major influential factors and the potential impact of changes to these factors on peak demand would underpin demand reduction intervention strategies for a wider target group.

Analysis of distributed beamforming in cooperative communications network with phase shifter based smart antenna nodes

This research study investigates the application of phase shifter-based smart antenna system in distributed beamforming. It examines the way to optimise the transmit power by jointly maximising the directivity of the array antennas and the weight vector for distributed beamforming. This research study concludes that maximising directivity can lead to better transmit power minimisation compared to maximising field intensity. This study also concludes that signal to noise power ratio maximisation subject to a power constraint and power minimisation subject to a signal to noise power ratio constraint yield the same results.