Introduction

Australian perspectives and practices within early childhood education and care are underpinned by understandings of children, how they learn, their emotional and physical needs and their connectedness to family and their communities. There is strong international research evidence supporting the value of providing high quality and accessible early childhood education and care, and this evidence base continues to grow. Drawing on international and Australian research, this book provides an introduction to this complex and multifaceted field.

A Story of Organized Crime: Constructing Criminality and Building Institutions

This is a narrative about the way in which a category of crime-to-be-combated is constructed through the discipline of criminology and the agents of discipline in criminal justice. The aim was to examine organized crime through the eyes of those whose job it is to fight it (and define it), and in doing so investigate the ways social problems surface as sites for state intervention. A genealogy of organized crime within criminological thought was completed, demonstrating that there are a range of different ways organized crime has been constructed within the social scientific discipline, and each of these were influenced by the social context, political winds and intellectual climate of the time. Following this first finding, in-depth qualitative interviews were conducted with individuals who had worked at the apex of the policing of organized crime in Australia, in order to trace their understandings of organized crime across recent history. It was found that organized crime can be understood as an object of the discourse of the politics of law and order, the discourse of international securitization, new public management in policing business, and involves the forging of outlaw identities. Therefore, there are multiple meanings of organized crime that have arisen from an interconnected set of social, political, moral and bureaucratic discourses. The institutional response to organized crime, including law and policing, was subsequently examined. An extensive legislative framework has been enacted at multiple jurisdictional levels, and the problem of organized crime was found to be deserving of unique institutional powers and configurations to deal with it. The social problem of organized crime, as constituted by the discourses mapped out in this research, has led to a new generation of increasingly preemptive and punitive laws, and the creation of new state agencies with amplified powers. That is, the response to organized crime, with a focus on criminalization and enforcement, has been driven and shaped by the four discourses and the way in which the phenomenon is constructed within them. An appreciation of the nexus between the emergence of the social problem, and the formation of institutions in response to it, is important in developing a more complete understanding of the various dimensions of organized crime.

Autonomous UAVs wildlife detection using thermal imaging, predictive navigation and computer vision

There is an increased interest on the use of Unmanned Aerial Vehicles (UAVs) for wildlife and feral animal monitoring around the world. This paper describes a novel system which uses a predictive dynamic application that places the UAV ahead of a user, with a low cost thermal camera, a small onboard computer that identifies heat signatures of a target animal from a predetermined altitude and transmits that target’s GPS coordinates. A map is generated and various data sets and graphs are displayed using a GUI designed for easy use. The paper describes the hardware and software architecture and the probabilistic model for downward facing camera for the detection of an animal. Behavioral dynamics of target movement for the design of a Kalman filter and Markov model based prediction algorithm are used to place the UAV ahead of the user. Geometrical concepts and Haversine formula are applied to the maximum likelihood case in order to make a prediction regarding a future state of the user, thus delivering a new way point for autonomous navigation. Results show that the system is capable of autonomously locating animals from a predetermined height and generate a map showing the location of the animals ahead of the user.

Design and flight testing of a bio-inspired plume tracking algorithm for unmanned serial vehicles

There is an increased interest on the use of UAVs for environmental research such as tracking bush fires, volcanic eruptions, chemical accidents or pollution sources. The aim of this paper is to describe the theory and results of a bio-inspired plume tracking algorithm. A method for generating sparse plumes in a virtual environment was also developed. Results indicated the ability of the algorithms to track plumes in 2D and 3D. The system has been tested with hardware in the loop (HIL) simulations and in flight using a CO2 gas sensor mounted to a multi-rotor UAV. The UAV is controlled by the plume tracking algorithm running on the ground control station (GCS).

MPC controlled multirotor with suspended slung load: System architecture and visual load detection

There is an increased interest in the use of Unmanned Aerial Vehicles for load transportation from environmental remote sensing to construction and parcel delivery. One of the main challenges is accurate control of the load position and trajectory. This paper presents an assessment of real flight trials for the control of an autonomous multi-rotor with a suspended slung load using only visual feedback to determine the load position. This method uses an onboard camera to take advantage of a common visual marker detection algorithm to robustly detect the load location. The load position is calculated using an onboard processor, and transmitted over a wireless network to a ground station integrating MATLAB/SIMULINK and Robotic Operating System (ROS) and a Model Predictive Controller (MPC) to control both the load and the UAV. To evaluate the system performance, the position of the load determined by the visual detection system in real flight is compared with data received by a motion tracking system. The multi-rotor position tracking performance is also analyzed by conducting flight trials using perfect load position data and data obtained only from the visual system. Results show very accurate estimation of the load position (~5% Offset) using only the visual system and demonstrate that the need for an external motion tracking system is not needed for this task.

Policing expert testimony in a death investigation: Medical opinion as legal fact

Within coronial investigations, pathologists are called upon to given evidence as to cause of death. This evidence is given great weight by the coroners; after all, scientific ‘truth’ is widely deemed to be far more reliable than legal ‘opinion’. The purpose of this paper is to examine the ontological and epistemological status of that evidence, from the perspectives of both the pathologists and the coroners. As part of an Australian Research Council Linkage Grant, interviews were conducted with seven pathologists and 10 coroners from within the Queensland coronial system. Contrary to expectations, and the work of philosophers of science, such as Feyerabend (1975), pathologists did not present their findings in terms of unequivocal facts or objective truths relating to causes of death. Rather, their evidence was largely presented as ‘educated opinion’ based upon ‘the weight of evidence’. It was actually the coroners who translated that opinion into ‘medical fact’ within the proceedings of their death investigations, arguably as a consequence of the administrative necessity to reach a clear-cut finding as to cause of death, and on the basis of their own understanding of the ontology of medical knowledge. These findings support Latour’s (2010) claim that law requires a fundamentally different epistemology to science, and that science is not entirely to blame for the extravagant truth-claims made on its behalf

Unmanned Aerial Vehicles (UAVs) and artificial intelligence revolutionizing wildlife monitoring and conservation

Surveying threatened and invasive species to obtain accurate population estimates is an important but challenging task that requires a considerable investment in time and resources. Estimates using existing ground-based monitoring techniques, such as camera traps and surveys performed on foot, are known to be resource intensive, potentially inaccurate and imprecise, and difficult to validate. Recent developments in unmanned aerial vehicles (UAV), artificial intelligence and miniaturized thermal imaging systems represent a new opportunity for wildlife experts to inexpensively survey relatively large areas. The system presented in this paper includes thermal image acquisition as well as a video processing pipeline to perform object detection, classification and tracking of wildlife in forest or open areas. The system is tested on thermal video data from ground based and test flight footage, and is found to be able to detect all the target wildlife located in the surveyed area. The system is flexible in that the user can readily define the types of objects to classify and the object characteristics that should be considered during classification.

Open source computer-vision based guidance system for UAVs on-board decision making

The use of UAVs for remote sensing tasks; e.g. agriculture, search and rescue is increasing. The ability for UAVs to autonomously find a target and perform on-board decision making, such as descending to a new altitude or landing next to a target is a desired capability. Computer-vision functionality allows the Unmanned Aerial Vehicle (UAV) to follow a designated flight plan, detect an object of interest, and change its planned path. In this paper we describe a low cost and an open source system where all image processing is achieved on-board the UAV using a Raspberry Pi 2 microprocessor interfaced with a camera. The Raspberry Pi and the autopilot are physically connected through serial and communicate via MAVProxy. The Raspberry Pi continuously monitors the flight path in real time through USB camera module. The algorithm checks whether the target is captured or not. If the target is detected, the position of the object in frame is represented in Cartesian coordinates and converted into estimate GPS coordinates. In parallel, the autopilot receives the target location approximate GPS and makes a decision to guide the UAV to a new location. This system also has potential uses in the field of Precision Agriculture, plant pest detection and disease outbreaks which cause detrimental financial damage to crop yields if not detected early on. Results show the algorithm is accurate to detect 99% of object of interest and the UAV is capable of navigation and doing on-board decision making.

The creative suburb: Building and urban designs for suburban innovators

Influential creative industries and creative place thinkers Richard Florida and Charles Landry agree that creativity is necessary for a prospering liveable and, therefore, sustainable city. Following Florida’s work, the ‘creative class’ has become central to what has turned out to be city-centre-centric growth policies. However, until the Queensland University of Technology’s Australian Research Council sponsored research into “creative suburbia”, few researchers had demonstrated – let alone challenged – the notion that a substantial cohort of creative industries workers might prefer to live and work at home in the suburbs rather than in city centres. The “creative suburb” work builds on the creative suburbia research. In a practice-led and property development industry embedded inquiry, the creative suburb draws on significant primary research with suburban, home-based, creative industries workers, vernacular architecture, and town planning in the Toowoomba region, in the state of Queensland, Australia, as inspiration for a series of new building and urban designs available for innovators operating in new suburban greenfield situations and suburban areas undergoing a refit in Queensland and possibly further afield. This paper focuses on one building design informed by this inquiry, with the intention of its construction as a ’showcasestudy’ ‘homeworkhouse’, suitable for creative industries workers in the Toowoomba region.

Participatory media and 'co-creative' storytelling

Distinguishing critical participatory media from other participatory media forms (for example user-generated content and social media) may be increasingly difficult to do, but nonetheless remains an important task if media studies is to remain relevant to the continuing development of inclusive social political and media cultures. This was one of a number of the premises for a national Australian Research Council-funded study that set out to improve the visibility of critical participatory media, and understand its use for facilitating media participation on a population wide basis (Spurgeon et. al. 2015). The term ‘co-creative’ media was adopted to make this distinction and to describe an informal system of critical participatory media practice that is situated between major public, Indigenous and community arts, culture and media sectors. Although the co-creative media system is found to be a site of innovation and engine for social change its value is still not fully understood. For this reason, this system continues to provide media and cultural studies scholars with valuable sites for researching the sociocultural transformations afforded by new media and communication technologies, as well as their limitations.

Development of a robust framework for an outdoor mobile manipulation UAV

There is a growing interest to autonomously collect or manipulate objects in remote or unknown environments, such as mountains, gullies, bush-land, or rough terrain. There are several limitations of conventional methods using manned or remotely controlled aircraft. The capability of small Unmanned Aerial Vehicles (UAV) used in parallel with robotic manipulators could overcome some of these limitations. By enabling the autonomous exploration of both naturally hazardous environments, or areas which are biologically, chemically, or radioactively contaminated, it is possible to collect samples and data from such environments without directly exposing personnel to such risks. This paper covers the design, integration, and initial testing of a framework for outdoor mobile manipulation UAV. The framework is designed to allow further integration and testing of complex control theories, with the capability to operate outdoors in unknown environments. The results obtained act as a reference for the effectiveness of the integrated sensors and low-level control methods used for the preliminary testing, as well as identifying the key technologies needed for the development of an outdoor capable system.

Uncertainty based online planning for UAV target finding in cluttered and GPS-denied environments

There are some scenarios in which Unmmaned Aerial Vehicle (UAV) navigation becomes a challenge due to the occlusion of GPS systems signal, the presence of obstacles and constraints in the space in which a UAV operates. An additional challenge is presented when a target whose location is unknown must be found within a confined space. In this paper we present a UAV navigation and target finding mission, modelled as a Partially Observable Markov Decision Process (POMDP) using a state-of-the-art online solver in a real scenario using a low cost commercial multi rotor UAV and a modular system architecture running under the Robotic Operative System (ROS). Using POMDP has several advantages to conventional approaches as they take into account uncertainties in sensor information. We present a framework for testing the mission with simulation tests and real flight tests in which we model the system dynamics and motion and perception uncertainties. The system uses a quad-copter aircraft with an board downwards looking camera without the need of GPS systems while avoiding obstacles within a confined area. Results indicate that the system has 100% success rate in simulation and 80% rate during flight test for finding targets located at different locations.

Deploying speaker verification techniques to vision-based RPA detect and avoid

Detect and Avoid (DAA) technology is widely acknowledged as a critical enabler for unsegregated Remote Piloted Aircraft (RPA) operations, particularly Beyond Visual Line of Sight (BVLOS). Image-based DAA, in the visible spectrum, is a promising technological option for addressing the challenges DAA presents. Two impediments to progress for this approach are the scarcity of available video footage to train and test algorithms, in conjunction with testing regimes and specifications which facilitate repeatable, statistically valid, performance assessment. This paper includes three key contributions undertaken to address these impediments. In the first instance, we detail our progress towards the creation of a large hybrid collision and near-collision encounter database. Second, we explore the suitability of techniques employed by the biometric research community (Speaker Verification and Language Identification), for DAA performance optimisation and assessment. These techniques include Detection Error Trade-off (DET) curves, Equal Error Rates (EER), and the Detection Cost Function (DCF). Finally, the hybrid database and the speech-based techniques are combined and employed in the assessment of a contemporary, image based DAA system. This system includes stabilisation, morphological filtering and a Hidden Markov Model (HMM) temporal filter.

Aircraft trajectory clustering techniques using circular statistics

This paper presents a statistical aircraft trajectory clustering approach aimed at discriminating between typical manned and expected unmanned traffic patterns. First, a resampled version of each trajectory is modelled using a mixture of Von Mises distributions (circular statistics). Second, the remodelled trajectories are globally aligned using tools from bioinformatics. Third, the alignment scores are used to cluster the trajectories using an iterative k-medoids approach and an appropriate distance function. The approach is then evaluated using synthetically generated unmanned aircraft flights combined with real air traffic position reports taken over a sector of Northern Queensland, Australia. Results suggest that the technique is useful in distinguishing between expected unmanned and manned aircraft traffic behaviour, as well as identifying some common conventional air traffic patterns.

Simulation and modelling tools for quantitative safety assessments of unmanned aircraft systems and operations

This paper presents two simple simulation and modelling tools designed to aid in the safety assessment required for unmanned aircraft operations within unsegregated airspace. First, a fast pair-wise encounter generator is derived to simulate the See and Avoid environment. The utility of the encounter generator is demonstrated through the development of a hybrid database and a statistical performance evaluation of an autonomous See and Avoid decision and control strategy. Second, an unmanned aircraft mission generator is derived to help visualise the impact of multiple persistent unmanned operations on existing air traffic. The utility of the mission generator is demonstrated through an example analysis of a mixed airspace environment using real traffic data in Australia. These simulation and modelling approaches constitute a useful and extensible set of analysis tools, that can be leveraged to help explore some of the more fundamental and challenging problems facing civilian unmanned aircraft system integration.