FixVegas : facilitating multi-directional communication between government officials and citizens to support urban planning in the city of Brisbane

The goal of this project was to develop a mobile application for the iOS platform, that would support the partner of this project, the Brisbane City Council, in stronger engage citizens in participating in urban planning and development projects. The resulting application is an extended version of FixVegas, a system that allows citizens to report maintenance request to the Brisbane City Council through their smartphone. The new version of the system makes all incoming requests publicly available within the application, allows users to support, comment or disapprove of these. As an addition, the concept of the idea has been introduced. Citizens can submit suggestions for improving the city to the municipality, discuss them with other fellow citizens and, ideally, also with Council representatives. The city officials as well are provided with the ability of publishing development project as an idea and let citizens deliberate it. This way, bidirectional communication between these two parties is created. A web interface complements the iPhone application. The system has been developed after the principle of User Centered Design, by assessing user needs, creating and evaluating prototypes and conducting a user study. The study showed that FixVegas2 has been perceived as an enhancement compared to the previous version, and that the idea concept has been received on a positive note. Indepth questions, such as the influence the system could have on community dynamics or the public participation in urban planning projects could only hardly investigated. However, these findings can be achieved by the alternative study designs that have been proposed.

Traffic state estimation from partial Bluetooth and volume observations : case study in the Brisbane metropolitan area

The application of the Bluetooth (BT) technology to transportation has been enabling researchers to make accurate travel time observations, in freeway and arterial roads. The Bluetooth traffic data are generally incomplete, for they only relate to those vehicles that are equipped with Bluetooth devices, and that are detected by the Bluetooth sensors of the road network. The fraction of detected vehicles versus the total number of transiting vehicles is often referred to as Bluetooth Penetration Rate (BTPR). The aim of this study is to precisely define the spatio-temporal relationship between the quantities that become available through the partial, noisy BT observations; and the hidden variables that describe the actual dynamics of vehicular traffic. To do so, we propose to incorporate a multi- class traffic model into a Sequential Montecarlo Estimation algorithm. Our framework has been applied for the empirical travel time investigations into the Brisbane Metropolitan region.

A multi-touch notice board fostering social interaction

We report on an alternative OCGM interface for a bulletin board, where a user can pin a note or a drawing, and actually shares contents. Exploiting direct and continuous manipulations, opposite to discrete gestures, to explore containers, the proposed interface supports a more natural and immediate interaction. It manages also the presence of different simultaneous users, allowing for the creation of local multimedia contents, the connection to social networks, providing a suitable working environment for cooperative and collaborative tasks in a multi-touch setup, such as touch-tables, interactive walls or multimedia boards

Efficacy of a children's procedural preparation and distraction device on healing in acute burn wound care procedures : study protocol for a randomized controlled trial

BACKGROUND: The intense pain and anxiety triggered by burns and their associated wound care procedures are well established in the literature. Non-pharmacological intervention is a critical component of total pain management protocols and is used as an adjunct to pharmacological analgesia. An example is virtual reality, which has been used effectively to dampen pain intensity and unpleasantness. Possible links or causal relationships between pain/anxiety/stress and burn wound healing have previously not been investigated. The purpose of this study is to investigate these relationships, specifically by determining if a newly developed multi-modal procedural preparation and distraction device (Ditto) used during acute burn wound care procedures will reduce the pain and anxiety of a child and increase the rate of re-epithelialization. METHODS/DESIGN: Children (4 to 12 years) with acute burn injuries presenting for their first dressing change will be randomly assigned to either the (1) Control group (standard distraction) or (2) Ditto intervention group (receiving Ditto, procedural preparation and Ditto distraction). It is intended that a minimum of 29 participants will be recruited for each treatment group. Repeated measures of pain intensity, anxiety, stress and healing will be taken at every dressing change until complete wound re-epithelialization. Further data collection will aid in determining patient satisfaction and cost effectiveness of the Ditto intervention, as well as its effect on speed of wound re-epithelialization. DISCUSSION: Results of this study will provide data on whether the disease process can be altered by reducing stress, pain and anxiety in the context of acute burn wounds. TRIAL REGISTRATION: ACTRN12611000913976.

Decision fusion from parts and samples for robust iris recognition

Fusion techniques can be used in biometrics to achieve higher accuracy. When biometric systems are in operation and the threat level changes, controlling the trade-off between detection error rates can reduce the impact of an attack. In a fused system, varying a single threshold does not allow this to be achieved, but systematic adjustment of a set of parameters does. In this paper, fused decisions from a multi-part, multi-sample sequential architecture are investigated for that purpose in an iris recognition system. A specific implementation of the multi-part architecture is proposed and the effect of the number of parts and samples in the resultant detection error rate is analysed. The effectiveness of the proposed architecture is then evaluated under two specific cases of obfuscation attack: miosis and mydriasis. Results show that robustness to such obfuscation attacks is achieved, since lower error rates than in the case of the non-fused base system are obtained.

Datasets for the evaluation of multi-sensor perception in natural environments with challenging conditions

This paper presents large, accurately calibrated and time-synchronised datasets, gathered outdoors in controlled environmental conditions, using an unmanned ground vehicle (UGV), equipped with a wide variety of sensors. It discusses how the data collection process was designed, the conditions in which these datasets have been gathered, and some possible outcomes of their exploitation, in particular for the evaluation of performance of sensors and perception algorithms for UGVs.

Sensor Data Integrity : Multi-Sensor Perception for Unmanned Ground Vehicles

This document describes large, accurately calibrated and time-synchronised datasets, gathered in controlled environmental conditions, using an unmanned ground vehicle equipped with a wide variety of sensors. These sensors include: multiple laser scanners, a millimetre wave radar scanner, a colour camera and an infra-red camera. Full details of the sensors are given, as well as the calibration parameters needed to locate them with respect to each other and to the platform. This report also specifies the format and content of the data, and the conditions in which the data have been gathered. The data collection was made in two different situations of the vehicle: static and dynamic. The static tests consisted of sensing a fixed ’reference’ terrain, containing simple known objects, from a motionless vehicle. For the dynamic tests, data were acquired from a moving vehicle in various environments, mainly rural, including an open area, a semi-urban zone and a natural area with different types of vegetation. For both categories, data have been gathered in controlled environmental conditions, which included the presence of dust, smoke and rain. Most of the environments involved were static, except for a few specific datasets which involve the presence of a walking pedestrian. Finally, this document presents illustrations of the effects of adverse environmental conditions on sensor data, as a first step towards reliability and integrity in autonomous perceptual systems.

Forming a joint venture project team for multi-discipline engineering services in Australia

Joint venture design teams are formed to combine resources and expertise in order to secure multi-discipline engineering design services on major projects. Bringing together resources from two ordinarily competing companies to form one joint team is however challenging as each parent company brings to the project its own organisational culture, processes and team attitudes. This study examined the factors that impact on forming a successful joint venture project team. Three critical areas were identified from an extensive literature review; Joint Venture Arrangements, Parent Companies and Forming the Team; and a survey was conducted with professionals who have worked in joint venture project teams in the Australian building industry in order to identify factors that affected successful joint venture team formation, and the common lessons learnt. This study reinforced the importance of three key criteria - trust, commitment and compatibility - for partner alignment. The results also identified four key lessons learnt which included; selecting the right resources, enabling a collaborative working environment by way of project office, implementing an independent Joint Venture Manager, and allocating work which is best for project with fees reflecting risk where risk is disproportionate.

The Marulan data sets: multi-sensor perception in a natural environment with challenging conditions

In this paper we present large, accurately calibrated and time-synchronized data sets, gathered outdoors in controlled and variable environmental conditions, using an unmanned ground vehicle (UGV), equipped with a wide variety of sensors. These include four 2D laser scanners, a radar scanner, a color camera and an infrared camera. It provides a full description of the system used for data collection and the types of environments and conditions in which these data sets have been gathered, which include the presence of airborne dust, smoke and rain.

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

Improved rural health through a collaborative model of care – qualitative findings

INTRODUCTION Health disparity between urban and rural regions in Australia is well-documented. In the Wheatbelt catchments of Western Australia there is higher incidence and rate of avoidable hospitalisation for chronic diseases. Structured care approach to chronic illnesses is not new but the focus has been on single disease state. A recent ARC Discovery Project on general practice nurse-led chronic disease management of diabetes, hypertension and stable ischaemic heart disease reported improved communication and better medical administration.[1] In our study we investigated the sustainability of such a multi-morbidities general practice –led collaborative model of care in rural Australia. METHODS A QUAN(qual) design was utilised. Eight pairs of rural general practices were matched. Inclusion criteria used were >18 years and capable of giving informed consent, at least one identified risk factor or diagnosed with chronic conditions. Patients were excluded if deemed medically unsuitable. A comprehensive care plan was formulated by the respective general practice nurse in consultation with the treating General Practitioner (GP) and patient based on the individual’s readiness to change, and was informed by available local resource. A case management approach was utilised. Shediaz-Rizkallah and Lee’s conceptual framework on sustainability informed our evaluation.[2] Our primary outcome on measures of sustainability was reduction in avoidable hospitalisation. Secondary outcomes were patients and practitioners acceptance and satisfaction, and changes to pre-determined interim clinical and process outcomes. RESULTS The qualitative interviews highlighted the community preference for a ‘sustainable’ local hospital in addition to general practice. Costs, ease of access, low prioritisation of self chronic care, workforce turnover and perception of losing another local resource if underutilised influenced the respondents’ decision to present at local hospital for avoidable chronic diseases regardless. CONCLUSIONS Despite the pragmatic nature of rural general practice in Australia, the sustainability of chronic multi-morbidities management in general practice require efficient integration of primary-secondary health care and consideration of other social determinants of health. What this study adds: What is already known on this subject: Structured approach to chronic disease management is not new and has been shown to be effective for reducing hospitalisation. However, the focus has been on single disease state. What does this study add: Sustainability of collaborative model of multi-morbidities care require better primary-secondary integration and consideration of social determinants of health.

Vulnerability and damage analysis of reinforced concrete framed buildings subjected to near field blast events

Terrorists usually target high occupancy iconic and public buildings using vehicle borne incendiary devices in order to claim a maximum number of lives and cause extensive damage to public property. While initial casualties are due to direct shock by the explosion, collapse of structural elements may extensively increase the total figure. Most of these buildings have been or are built without consideration of their vulnerability to such events. Therefore, the vulnerability and residual capacity assessment of buildings to deliberately exploded bombs is important to provide mitigation strategies to protect the buildings' occupants and the property. Explosive loads and their effects on a building have therefore attracted significant attention in the recent past. Comprehensive and economical design strategies must be developed for future construction. This research investigates the response and damage of reinforced concrete (RC) framed buildings together with their load bearing key structural components to a near field blast event. Finite element method (FEM) based analysis was used to investigate the structural framing system and components for global stability, followed by a rigorous analysis of key structural components for damage evaluation using the codes SAP2000 and LS DYNA respectively. The research involved four important areas in structural engineering. They are blast load determination, numerical modelling with FEM techniques, material performance under high strain rate and non-linear dynamic structural analysis. The response and damage of a RC framed building for different blast load scenarios were investigated. The blast influence region for a two dimensional RC frame was investigated for different load conditions and identified the critical region for each loading case. Two types of design methods are recommended for RC columns to provide superior residual capacities. They are RC columns detailing with multi-layer steel reinforcement cages and a composite columns including a central structural steel core. These are to provide post blast gravity load resisting capacity compared to typical RC column against a catastrophic collapse. Overall, this research broadens the current knowledge of blast and residual capacity analysis of RC framed structures and recommends methods to evaluate and mitigate blast impact on key elements of multi-storey buildings.

Voltage regulation, power balancing and battery storage discharge control by smart demand side management and multi-objective decision making

A novel intelligent online demand side management system is proposed for peak load management. The method also regulates the network voltage, balances the power in three phases and coordinates the battery storage discharge within the network. This method uses low cost controllers with low bandwidth two-way communication installed in costumers' premises and at distribution transformers to manage the peak load while maximizing customer satisfaction. A multi-objective decision making process is proposed to select the load(s) to be delayed or controlled. The efficacy of the proposed control system is verified through an event-based developed simulation in Matlab.

Hybrid multi-channel cooperative spectrum sensing to satisfy channel target

Spectrum sensing of multiple primary user channels is a crucial function in cognitive radio networks. In this paper we propose an optimal, sensing resource allocation algorithm for multi-channel cooperative spectrum sensing. The channel target is implemented as an objective and constraint to ensure a pre-determined number of empty channels are detected for secondary user network operations. Based on primary user traffic parameters, we calculate the minimum number of primary user channels that must be sensed to satisfy the channel target. We implement a hybrid sensing structure by grouping secondary user nodes into clusters and assign each cluster to sense a different primary user channels. We then solve the resource allocation problem to find the optimal sensing configuration and node allocation to minimise sensing duration. Simulation results show that the proposed algorithm requires the shortest sensing duration to achieve the channel target compared to existing studies that require long sensing and cannot guarantee the target.

Strategic capability development : a multi-level case study of the role of knowledge integration within product innovation

Capability development is at the heart of creating competitive advantage. This thesis intends to conceptualise Strategic Capability Development as a renewal of an organisation's existing capability in line with the requirements of the market. It followed and compared four product innovation projects within Iran Khodro Company (IKCO), an exemplar of capability development within the Iranian Auto industry. Findings show that the maturation of strategic capability at the organisational level has occurred through a sequence of product innovation projects and by dynamically shaping the learning and knowledge integration processes in accordance with emergence of the new structure within the industry. Accordingly, Strategic Capability Development is conceptualised in an interpretive model. Such findings are useful for development of an explanatory model and a practical capability development framework for managing learning and knowledge across different product innovation projects.