Droop control of converter interfaced micro sources in rural distributed generation

This paper proposes new droop control methods for load sharing in a rural area with distributed generation. Highly resistive lines, typical of rural low voltage networks, always create a big challenge for conventional droop control. To overcome the conflict between higher feedback gain for better power sharing and system stability in angle droop, two control methods have been proposed. The first method considers no communication among the distributed generators (DGs) and regulates the converter output voltage and angle ensuring proper sharing of load in a system having strong coupling between real and reactive power due to high line resistance. The second method, based on a smattering of communication, modifies the reference output volt-age angle of the DGs depending on the active and reactive power flow in the lines connected to point of common coupling (PCC). It is shown that with the second proposed control method, an economical and minimum communication system can achieve significant improvement in load sharing. The difference in error margin between proposed control schemes and a more costly high bandwidth communication system is small and the later may not be justified considering the increase in cost. The proposed control shows stable operation of the system for a range of operating conditions while ensuring satisfactory load sharing.

Creative Commons : the next generation : Creative Commons licence use five years on

Since its launch in 2001, the Creative Commons open content licensing initiative has received both praise and censure. While some have touted it as a major step towards removing the burdens copyright law imposes on creativity and innovation in the digital age, others have argued that it robs artists of their rightful income. This paper aims to provide a brief overview and analysis of the practical application of the Creative Commons licences five years after their launch. It looks at how the Creative Commons licences are being used and who is using them, and attempts to identify likely motivations for doing so. By identifying trends in how this licence use has changed over time, it also attempts to rebut arguments that Creative Commons is a movement of academics and hobbyists, and has no value for traditional organisations or working artists.

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.

Next Generation ‘Filmmaking’: New Markets, New Methods and New Business Models

Digital production and distribution technologies may create new opportunities for filmmaking in Australia. A culture of new approaches to filmmaking is emerging driven by ‘next generation filmmakers’ who are willing to consider new business models: from online web series to short films produced for mobile phones. At the same time cultural representation itself is transforming within an interactive, social media driven environment. Yet there is very little research into next generation filmmaking. The aim of this paper is to scope and discuss three key aspects of next generation filmmaking, namely: digital trends in film distribution and marketing; processes and strategies of ‘next generation’ filmmakers; and case studies of viable next generation business models and filmmaking practices. We conclude with a brief examination of the implications for media and cultural policy which suggests the future possibility of a rapprochement between creative industries discourse and cultural policy.

Anticipatory timing in algorithmic rhythm generation

Generative music algorithms frequently operate by making musical decisions in a sequence, with each step of the sequence incorporating the local musical context in the decision process. The context is generally a short window of past musical actions. What is not generally included in the context is future actions. For real-time systems this is because the future is unknown. Offline systems also frequently utilise causal algorithms either for reasons of efficiency [1] or to simulate perceptual constraints [2]. However, even real-time agents can incorporate knowledge of their own future actions by utilising some form of planning. We argue that for rhythmic generation the incorporation of a limited form of planning - anticipatory timing - offers a worthwhile trade-off between musical salience and efficiency. We give an example of a real-time generative agent - the Jambot - that utilises anticipatory timing for rhythmic generation. We describe its operation, and compare its output with and without anticipatory timing.

Transition pedagogy : a third generation approach to FYE : a case study of policy and practice for the higher education sector

Current research and practice related to the first year experience (FYE) of commencing higher education students are still mainly piecemeal rather than institution-wide with institutions struggling to achieve cross-institutional integration, coordination and coherence of FYE policy and practice. Drawing on a decade of FYE-related research including an ALTC Senior Fellowship and evidence at a large Australian metropolitan university, this paper explores how one institution has addressed that issue by tracing the evolution and maturation of strategies that ultimately conceptualize FYE as “everybody's business.” It is argued that, when first generation co-curricular and second generation curricular approaches are integrated and implemented through an intentionally designed curriculum by seamless partnerships of academic and professional staff in a whole-of-institution transformation, we have a third generation approach labelled here as transition pedagogy. It is suggested that transition pedagogy provides the optimal vehicle for dealing with the increasingly diverse commencing student cohorts by facilitating a sense of engagement, support and belonging. What is presented here is an example of transition pedagogy in action.

Testing of a distributed generation system with a virtual grid

The paper proposes a solution for testing of a physical distributed generation system (DGs) along with a computer simulated network. The computer simulated network is referred as the virtual grid in this paper. Integration of DG with the virtual grid provides broad area of testing of power supplying capability and dynamic performance of a DG. It is shown that a DG can supply a part of load power while keeping Point of Common Coupling (PCC) voltage magnitude constant. To represent the actual load, a universal load along with power regenerative capability is designed with the help of voltage source converter (VSC) that mimics the load characteristic. The overall performance of the proposed scheme is verified using computer simulation studies.

A hidden Markov model and relative entropy rate approach to vision-based dim target detection for UAV sense-and-avoid

Uninhabited aerial vehicles (UAVs) are a cutting-edge technology that is at the forefront of aviation/aerospace research and development worldwide. Many consider their current military and defence applications as just a token of their enormous potential. Unlocking and fully exploiting this potential will see UAVs in a multitude of civilian applications and routinely operating alongside piloted aircraft. The key to realising the full potential of UAVs lies in addressing a host of regulatory, public relation, and technological challenges never encountered be- fore. Aircraft collision avoidance is considered to be one of the most important issues to be addressed, given its safety critical nature. The collision avoidance problem can be roughly organised into three areas: 1) Sense; 2) Detect; and 3) Avoid. Sensing is concerned with obtaining accurate and reliable information about other aircraft in the air; detection involves identifying potential collision threats based on available information; avoidance deals with the formulation and execution of appropriate manoeuvres to maintain safe separation. This thesis tackles the detection aspect of collision avoidance, via the development of a target detection algorithm that is capable of real-time operation onboard a UAV platform. One of the key challenges of the detection problem is the need to provide early warning. This translates to detecting potential threats whilst they are still far away, when their presence is likely to be obscured and hidden by noise. Another important consideration is the choice of sensors to capture target information, which has implications for the design and practical implementation of the detection algorithm. The main contributions of the thesis are: 1) the proposal of a dim target detection algorithm combining image morphology and hidden Markov model (HMM) filtering approaches; 2) the novel use of relative entropy rate (RER) concepts for HMM filter design; 3) the characterisation of algorithm detection performance based on simulated data as well as real in-flight target image data; and 4) the demonstration of the proposed algorithm's capacity for real-time target detection. We also consider the extension of HMM filtering techniques and the application of RER concepts for target heading angle estimation. In this thesis we propose a computer-vision based detection solution, due to the commercial-off-the-shelf (COTS) availability of camera hardware and the hardware's relatively low cost, power, and size requirements. The proposed target detection algorithm adopts a two-stage processing paradigm that begins with an image enhancement pre-processing stage followed by a track-before-detect (TBD) temporal processing stage that has been shown to be effective in dim target detection. We compare the performance of two candidate morphological filters for the image pre-processing stage, and propose a multiple hidden Markov model (MHMM) filter for the TBD temporal processing stage. The role of the morphological pre-processing stage is to exploit the spatial features of potential collision threats, while the MHMM filter serves to exploit the temporal characteristics or dynamics. The problem of optimising our proposed MHMM filter has been examined in detail. Our investigation has produced a novel design process for the MHMM filter that exploits information theory and entropy related concepts. The filter design process is posed as a mini-max optimisation problem based on a joint RER cost criterion. We provide proof that this joint RER cost criterion provides a bound on the conditional mean estimate (CME) performance of our MHMM filter, and this in turn establishes a strong theoretical basis connecting our filter design process to filter performance. Through this connection we can intelligently compare and optimise candidate filter models at the design stage, rather than having to resort to time consuming Monte Carlo simulations to gauge the relative performance of candidate designs. Moreover, the underlying entropy concepts are not constrained to any particular model type. This suggests that the RER concepts established here may be generalised to provide a useful design criterion for multiple model filtering approaches outside the class of HMM filters. In this thesis we also evaluate the performance of our proposed target detection algorithm under realistic operation conditions, and give consideration to the practical deployment of the detection algorithm onboard a UAV platform. Two fixed-wing UAVs were engaged to recreate various collision-course scenarios to capture highly realistic vision (from an onboard camera perspective) of the moments leading up to a collision. Based on this collected data, our proposed detection approach was able to detect targets out to distances ranging from about 400m to 900m. These distances, (with some assumptions about closing speeds and aircraft trajectories) translate to an advanced warning ahead of impact that approaches the 12.5 second response time recommended for human pilots. Furthermore, readily available graphic processing unit (GPU) based hardware is exploited for its parallel computing capabilities to demonstrate the practical feasibility of the proposed target detection algorithm. A prototype hardware-in- the-loop system has been found to be capable of achieving data processing rates sufficient for real-time operation. There is also scope for further improvement in performance through code optimisations. Overall, our proposed image-based target detection algorithm offers UAVs a cost-effective real-time target detection capability that is a step forward in ad- dressing the collision avoidance issue that is currently one of the most significant obstacles preventing widespread civilian applications of uninhabited aircraft. We also highlight that the algorithm development process has led to the discovery of a powerful multiple HMM filtering approach and a novel RER-based multiple filter design process. The utility of our multiple HMM filtering approach and RER concepts, however, extend beyond the target detection problem. This is demonstrated by our application of HMM filters and RER concepts to a heading angle estimation problem.

Refiguring the net generation : beyond users

In place of, or alongside paradigms such as "the net generation", we suggest that the full implications of the Internet might be productively analysed using a broader framework, that of social imaginaries. First used by Cornelius Castoriadis and more recently by Charles Taylor, the social imaginary, as applied here, is the loosely co-ordinated body of significations that enable our social acts and practices by making sense of them.