A generative design system based on evolutionary and mathematical functions

Previous work by Professor John Frazer on Evolutionary Architecture provides a basis for the development of a system evolving architectural envelopes in a generic and abstract manner. Recent research by the authors has focused on the implementation of a virtual environment for the automatic generation and exploration of complex forms and architectural envelopes based on solid modelling techniques and the integration of evolutionary algorithms, enhanced computational and mathematical models. Abstract data types are introduced for genotypes in a genetic algorithm order to develop complex models using generative and evolutionary computing techniques. Multi-objective optimisation techniques are employed for defining the fitness function in the evaluation process.

Contemporary issues in Australian family law: Do we need a more unified and interventionist judicial model

Recent decisions of the Family Court of Australian reflect concerns over the adversarial nature of the legal process. The processes and procedures of the judicial system militate against a detailed examination of the issues and rights of the parties in dispute. The limitations of the family law framework are particularly demonstrated in disputes over the custody of children where the Court has tended to neglect the rights and interests of the primary carer. An alternative "unified family court" framework will be examined in which the Court pursues a more active and interventionist approach in the determination of family law disputes.

Review of vibration-based damage detection and condition assessment of bridge structures using structural health monitoring

As a part of vital infrastructure and transportation networks, bridge structures must function safely at all times. However, due to heavier and faster moving vehicular loads and function adjustment, such as Busway accommodation, many bridges are now operating at an overload beyond their design capacity. Additionally, the huge renovation and replacement costs always make the infrastructure owners difficult to undertake. Structural health monitoring (SHM) is set to assess condition and foresee probable failures of designated bridge(s), so as to monitor the structural health of the bridges. The SHM systems proposed recently are incorporated with Vibration-Based Damage Detection (VBDD) techniques, Statistical Methods and Signal processing techniques and have been regarded as efficient and economical ways to solve the problem. The recent development in damage detection and condition assessment techniques based on VBDD and statistical methods are reviewed. The VBDD methods based on changes in natural frequencies, curvature/strain modes, modal strain energy (MSE) dynamic flexibility, artificial neural networks (ANN) before and after damage and other signal processing methods like Wavelet techniques and empirical mode decomposition (EMD) / Hilbert spectrum methods are discussed here.

Integrating Creative Practice and Research in the Digital Media Arts

Research is often characterised as the search for new ideas and understanding. The language of this view privileges the cognitive and intellectual aspects of discovery. However, in the research process theoretical claims are usually evaluated in practice and, indeed, the observations and experiences of practical circumstances often lead to new research questions. This feedback loop between speculation and experimentation is fundamental to research in many disciplines, and is also appropriate for research in the creative arts. In this chapter we will examine how our creative desire for artistic expressivity results in interplay between actions and ideas that direct the development of techniques and approaches for our audio/visual live-coding activities.

Race and equity in higher education : A harder path for Indigenous academics

Our experiences as Indigenous academics within universities often reflects the experiences we have as Indigenous people in broader society, yet I am still surprised and angered when it is others working in higher education who espouse notions of justice and equity with whom we experience tension and conflict in asserting our rights, values and cultural values. At times it is a constant struggle even when universities have Reconciliation Statements as most of them do now, Indigenous recruitment or employment strategies and university wide anti-racism and anti-discrimination policies and procedures.

Interventions for co-occurring addictive and other mental disorders (AMDs)

While research on the management of co-occurring addictive and mental disorders (AMDs) has grown substantially in recent years, we still have little guidance on specific strategies. Consideration of epidemiological research and ethical principles can supplement existing clinical trials in providing a way forward. High frequencies of co-occurring disorders, equity of access for affected individuals and potential clashes between services in priorities and procedures, suggest that a stepped model of care by a single service may often be required. Typically, problems are multiple rather than dual, with potential for mutual influence, suggesting a need for interventions that are sensitive to and encompass complex co-occurring problems. Motivational problems are endemic, initial gains are often partial and unstable, and relapses potentially have serious consequences, suggesting a need for long-term, assertive follow-up. Principles such as these provide a solid framework for designing both services and interventions. However, there is a continuing need for controlled trials that unpack effective components of interventions, and increase their impact.

Classification of Airborne LIDAR Intensity Data Using Statistical Analysis and Hough Transform with Application to Power Line Corridors

Light Detection and Ranging (LIDAR) has great potential to assist vegetation management in power line corridors by providing more accurate geometric information of the power line assets and vegetation along the corridors. However, the development of algorithms for the automatic processing of LIDAR point cloud data, in particular for feature extraction and classification of raw point cloud data, is in still in its infancy. In this paper, we take advantage of LIDAR intensity and try to classify ground and non-ground points by statistically analyzing the skewness and kurtosis of the intensity data. Moreover, the Hough transform is employed to detected power lines from the filtered object points. The experimental results show the effectiveness of our methods and indicate that better results were obtained by using LIDAR intensity data than elevation data.

Adaptive music techniques

There are many interactive media systems, including computer games and media art works, in which it is desirable for music to vary in response to changes in the environment. In this paper we will outline a range of algorithmic techniques that enable music to adapt to such changes, taking into account the need for the music to vary in its expressiveness or mood while remaining coherent and recognisable. We will discuss the approaches which we have arrived at after experience in a range of adaptive music systems over recent years, and draw upon these experiences to inform discussion of relevant considerations and to illustrate the techniques and their effect.

ePortfolios and preservice teachers : governing at a distance through non-human actors

This chapter seeks to develop an analysis of the contemporary use of the ePortfolio (Electronic Portfolio) in education practices. Unlike other explorations of this new technology which are deterministic in their approach, the authors seek to reveal the techniques and practices of government which underpin the implementation of the e-portfolio. By interrogating a specific case study example from a large Australian university’s preservice teacher program, the authors find that the e-portfolio is represented as eLearning technology but serves to govern students via autonomization and self responsibilization. Using policy data and other key documents, they are able to reveal the e-portfolio as a delegated authority in the governance of preservice teachers. However, despite this ongoing trend, they suggest that like other practices of government, the e-portfolio will eventually fail. This however the authors conclude opens up space for critical thought and engagement which is not afforded presently.

Improved simultaneous computation of motion detection and optical flow for object tracking

Object tracking systems require accurate segmentation of the objects from the background for effective tracking. Motion segmentation or optical flow can be used to segment incoming images. Whilst optical flow allows multiple moving targets to be separated based on their individual velocities, optical flow techniques are prone to errors caused by changing lighting and occlusions, both common in a surveillance environment. Motion segmentation techniques are more robust to fluctuating lighting and occlusions, but don't provide information on the direction of the motion. In this paper we propose a combined motion segmentation/optical flow algorithm for use in object tracking. The proposed algorithm uses the motion segmentation results to inform the optical flow calculations and ensure that optical flow is only calculated in regions of motion, and improve the performance of the optical flow around the edge of moving objects. Optical flow is calculated at pixel resolution and tracking of flow vectors is employed to improve performance and detect discontinuities, which can indicate the location of overlaps between objects. The algorithm is evaluated by attempting to extract a moving target within the flow images, given expected horizontal and vertical movement (i.e. the algorithms intended use for object tracking). Results show that the proposed algorithm outperforms other widely used optical flow techniques for this surveillance application.

Knowledge is not power, but it’s a start : young people and employment entitlements

This paper employs empirical evidence from a survey of Queensland secondary school students to examine their knowledge about their wages and working conditions. It does so within the theoretical lens of the Gagne (or Gagne-Briggs) theory of instruction, which centres on the content of learning and how learning is acquired (Gagne, Briggs & Wager, 1988). While Gagne articulates five categories of learning, our focus here is on two; verbal information or declarative knowledge (facts that people can declare), and procedural knowledge (the rules and procedures for achieving outcomes). We show that student workers know little about the instruments governing their employment, or their workplace entitlements. Of the total sample of year 9 and year 11 students surveyed (n=892), those students who worked, or who had worked in the past year (n=438), were asked to identify whether they were employed under an award, collective agreement or AWA. Eighty three per cent of students did not know which industrial instrument set their wages. We argue that if young workers do not have declarative knowledge of their entitlements, nor basic procedural knowledge about redress, then they are not in a position to deploy Gagne’s ‘cognitive strategies’ that would enable them to take action to ensure their working conditions meet legal minima. We advocate that young workers should be given summary information on their wages and other entitlements on appointment and that such summary information should be readily available on employers’ noticeboards and electronically on company websites, and that the information should include a brief summary of avenues for redressing issues of underpayment or sub-standard conditions.

Development and use of clinical guidelines

The purpose of this chapter is to provide an overview of the development and use of clinical guidelines as a tool for decision making in clinical practice. Nurses have always developed and used tools to guide clinical decision making related to interventions in practice. Since Florence Nightingale (Nightingale 1860) gave us ‘notes’ on nursing in the late 1800s, nurses have continued to use tools, such as standards, policies and procedures, protocols, algorithms, clinical pathways and clinical guidelines, to assist them in making appropriate decisions about patient care that eventuate in the best desired patient outcomes. Clinical guidelines have enjoyed growing popularity as a comprehensive tool for synthesising clinical evidence and information into user-friendly recommendations for practice. Historically, clinical guidelines were developed by individual experts or groups of experts by consensus, with no transparent process for the user to determine the validity and reliability of the recommendations. The acceptance of the evidence-based practice (EBP) movement as a paradigm for clinical decision making underscores the imperative for clinical guidelines to be systematically developed and based on the best available research evidence. Clinicians are faced with the dilemma of choosing from an abundance of guidelines of variable quality, or developing new guidelines. Where do you start? How do you find an existing guideline to fit your practice? How do you know if a guideline is evidence-based, valid and reliable? Should you apply an existing guideline in your practice or develop a new guideline? How do you get clinicians to use the guidelines? How do you know if using the guideline will make any difference in care delivery or patient outcomes? Whatever the choice, the challenge lies in choosing or developing a clinical guideline that is credible as a decision-making tool for the delivery of quality, efficient and effective care. This chapter will address the posed questions through an exploration of the ins and outs of clinical guidelines, from development to application to evaluation.

An evaluation of current and future botnet defenses

Botnets are large networks of compromised machines under the control of a bot master. These botnets constantly evolve their defences to allow the continuation of their malicious activities. The constant development of new botnet mitigation strategies and their subsequent defensive countermeasures has lead to a technological arms race, one which the bot masters have significant incentives to win. This dissertation analyzes the current and future states of the botnet arms race by introducing a taxonomy of botnet defences and a simulation framework for evaluating botnet techniques. The taxonomy covers current botnet techniques and highlights possible future techniques for further analysis under the simulation framework. This framework allows the evaluation of the effect techniques such as reputation systems and proof of work schemes have on the resources required to disable a peer-to-peer botnet. Given the increase in the resources required, our results suggest that the prospects of eliminating the botnet threat are limited.