Near real-time prediction of Zenith Tropospheric Delays for position estimation over long-baseline CORS network

This paper presents the preliminary results in establishing a strategy for predicting Zenith Tropospheric Delay (ZTD) and relative ZTD (rZTD) between Continuous Operating Reference Stations (CORS) in near real-time. It is anticipated that the predicted ZTD or rZTD can assist the network-based Real-Time Kinematic (RTK) performance over long inter-station distances, ultimately, enabling a cost effective method of delivering precise positioning services to sparsely populated regional areas, such as Queensland. This research firstly investigates two ZTD solutions: 1) the post-processed IGS ZTD solution and 2) the near Real-Time ZTD solution. The near Real-Time solution is obtained through the GNSS processing software package (Bernese) that has been deployed for this project. The predictability of the near Real-Time Bernese solution is analyzed and compared to the post-processed IGS solution where it acts as the benchmark solution. The predictability analyses were conducted with various prediction time of 15, 30, 45, and 60 minutes to determine the error with respect to timeliness. The predictability of ZTD and relative ZTD is determined (or characterized) by using the previously estimated ZTD as the predicted ZTD of current epoch. This research has shown that both the ZTD and relative ZTD predicted errors are random in nature; the STD grows from a few millimeters to sub-centimeters while the predicted delay interval ranges from 15 to 60 minutes. Additionally, the RZTD predictability shows very little dependency on the length of tested baselines of up to 1000 kilometers. Finally, the comparison of near Real-Time Bernese solution with IGS solution has shown a slight degradation in the prediction accuracy. The less accurate NRT solution has an STD error of 1cm within the delay of 50 minutes. However, some larger errors of up to 10cm are observed.

Open content creation : the issues of voice and the challenges of listening

This paper examines the proposition that increased ability to have a voice and be listened to, through ‘open ICT4D’ and ‘open content creation’ can be an effective mechanism for development. The paper discusses empirical work that strongly indicates that this only happens when voice is appropriately valued in the development process. Having a voice in development processes are less effective when participation is limited. Open ICT allows for more and more voices to be heard, but it is open ICT4D that has the obligation to ensure voices are listened to. In the paper I first explore participatory development and the idea of open ICT4D before elaborating on issues of voice and thinking about voice as process, and voice as value. Research findings are presented from research that experimented with participatory (or open) content creation, discussed in relation to notions of openness and voice. I then consider the challenges of listening, before drawing some conclusions about opening up ICT4D research.

Just Relations : Indigenous families in Australian lifestyle media

This paper argues that the increasing visibility of Indigenous families in the mainstream Australian media over the past ten years has produced new opportunities for addressing national injustices of the Stolen Generations. It shows how, as certain celebrities like Ernie Dingo, Nova Peris and Cathy Freeman, have become popular household names, a concurrent public interest in their family backgrounds has grown. Descriptive accounts of relationships and shared histories – propelled by the expansion of the lifestyle television genre in this context – has enabled some stories of the ‘Stolen Generations’ to be seen as ‘ordinary’, and part of a broader sense of everyday Australian life for the first time. With the aid of recent sexual citizenship research, the article illustrates that such middle-class representations give voice to new embodiments of citizenship in the post-apology era, making Indigenous justice more subjectively interconnected with life in the white Australian public sphere.

Preventing consumer credit over-commitment and irresponsible lending in Australia

Mirroring the trends in other developed countries, levels of household debt in Australia have risen markedly in recent years. As one example, the total amount lent by banks to individuals has risen from $175.5 billion in August 1995 to $590.5 billion in August 2005.1 Consumer groups an~ media commentators here have long raised concerns about the risks of increasing levels of household debt and over-commitment, linking these issues at least in part to irresponsible lending practices. And more recently, the Reserve Bank Governor has also expressed concerns about the ability 'of some households to manage if personal or economic circumstances change.2

Two voices : the marginalised body as a voice & Imperfect Offerings a novel

This thesis investigates the phenomenon of self-harm as a form of political protest using two different, but complementary, methods of inquiry: a theoretical research project and a novel. Through these two approaches, to the same research problem, I examine how we can re-position the body that self-harms in political protest from weapon to voice; and in doing so find a path towards ethical and equitable dialogue between marginalised and mainstream communities. The theoretical, or academic, portion of the thesis examines self-harm as protest, positing these acts as a form of tactical selfharm, and acknowledge its emergence as a voice for the otherwise silenced in the public sphere. Through the use of phenomenology and feminist theory I examine the body as site for political agency, the circumstances which surround the use of the body for protest, and the reaction to tactical self-harm by the individual and the state. Using Bakhtin’s concept of dialogism, and the dialogic space I propose that by ‘hearing’ the body engaged in tactical selfharm we come closer to entering into an ethical dialogue with the otherwise silenced in our communities (locally, nationally and globally). The novel, Imperfect Offerings, explores these ideas in a fictional world, and allows me to put faces, names and lives to those who are compelled to harm their bodies to be heard. Also using Bakhtin’s framework I encourage a dialogue between the critical and creative parts of the thesis, challenging the traditional paradigm of creative PhD projects as creative work and exegesis.

Improving automatic speaker verification using SVM techniques

Automatic recognition of people is an active field of research with important forensic and security applications. In these applications, it is not always possible for the subject to be in close proximity to the system. Voice represents a human behavioural trait which can be used to recognise people in such situations. Automatic Speaker Verification (ASV) is the process of verifying a persons identity through the analysis of their speech and enables recognition of a subject at a distance over a telephone channel { wired or wireless. A significant amount of research has focussed on the application of Gaussian mixture model (GMM) techniques to speaker verification systems providing state-of-the-art performance. GMM's are a type of generative classifier trained to model the probability distribution of the features used to represent a speaker. Recently introduced to the field of ASV research is the support vector machine (SVM). An SVM is a discriminative classifier requiring examples from both positive and negative classes to train a speaker model. The SVM is based on margin maximisation whereby a hyperplane attempts to separate classes in a high dimensional space. SVMs applied to the task of speaker verification have shown high potential, particularly when used to complement current GMM-based techniques in hybrid systems. This work aims to improve the performance of ASV systems using novel and innovative SVM-based techniques. Research was divided into three main themes: session variability compensation for SVMs; unsupervised model adaptation; and impostor dataset selection. The first theme investigated the differences between the GMM and SVM domains for the modelling of session variability | an aspect crucial for robust speaker verification. Techniques developed to improve the robustness of GMMbased classification were shown to bring about similar benefits to discriminative SVM classification through their integration in the hybrid GMM mean supervector SVM classifier. Further, the domains for the modelling of session variation were contrasted to find a number of common factors, however, the SVM-domain consistently provided marginally better session variation compensation. Minimal complementary information was found between the techniques due to the similarities in how they achieved their objectives. The second theme saw the proposal of a novel model for the purpose of session variation compensation in ASV systems. Continuous progressive model adaptation attempts to improve speaker models by retraining them after exploiting all encountered test utterances during normal use of the system. The introduction of the weight-based factor analysis model provided significant performance improvements of over 60% in an unsupervised scenario. SVM-based classification was then integrated into the progressive system providing further benefits in performance over the GMM counterpart. Analysis demonstrated that SVMs also hold several beneficial characteristics to the task of unsupervised model adaptation prompting further research in the area. In pursuing the final theme, an innovative background dataset selection technique was developed. This technique selects the most appropriate subset of examples from a large and diverse set of candidate impostor observations for use as the SVM background by exploiting the SVM training process. This selection was performed on a per-observation basis so as to overcome the shortcoming of the traditional heuristic-based approach to dataset selection. Results demonstrate the approach to provide performance improvements over both the use of the complete candidate dataset and the best heuristically-selected dataset whilst being only a fraction of the size. The refined dataset was also shown to generalise well to unseen corpora and be highly applicable to the selection of impostor cohorts required in alternate techniques for speaker verification.

Rephrasing voice : art, practice-led research and the limits and sites of articulacy

While my PhD is practice-led research, it is my contention that such an inquiry cannot develop as long as it tries to emulate other models of research. I assert that practice-led research needs to account for an epistemological unknown or uncertainty central to the practice of art. By focusing on what I call the artist's 'voice,' I will show how this 'voice' is comprised of a dual motivation—'articulate' representation and 'inarticulate' affect—which do not even necessarily derive from the artist. Through an analysis of art-historical precedents, critical literature (the work of Jean-François Lyotard and Andrew Benjamin, the critical methods of philosophy, phenomenology and psychoanalysis) as well as of my own painting and digital arts practice, I aim to demonstrate how this unknown or uncertain aspect of artistic inquiry can be mapped. It is my contention that practice-led research needs to address and account for this dualistic 'voice' in order to more comprehensively articulate its unique contribution to research culture.

Preliminary review of over-regulation in Australian financial services

This article examines a preliminary review and the limited evidence of over-regulation in Australian financial services. The 1997 Wallis Report and the CLERP 6 paper resulted in the amendments to Ch 7 of the Corporations Act 2001 (Cth) by the Financial Services Reform Act. Nearly a decade later the system based upon 'one-size fits all' dual track regime and a consistent licensing regime has greatly increased the costs of compliance. In the area of enforcement there has not been a dramatic change to the effective techniques applied by ASIC over other agencies such as APRA. In particular there are clear economic arguments, as well as international experiences which state that a single financial services regulator is more effective than the multi-layered approach adopted in Australia. Finally, in the superannuation area of financial services, which is worth A$800 billion there is unnecessary dual licensing and duplicated regulation with little evidence of any consumer-member benefit but at a much greater cost

Data muling over underwater wireless sensor networks using an autonomous underwater vehicle

We present algorithms, systems, and experimental results for underwater data muling. In data muling a mobile agent interacts with static agents to upload, download, or transport data to a different physical location. We consider a system comprising an Autonomous Underwater Vehicle (AUV) and many static Underwater Sensor Nodes (USN) networked together optically and acoustically. The AUV can locate the static nodes using vision and hover above the static nodes for data upload. We describe the hardware and software architecture of this underwater system, as well as experimental data. © 2006 IEEE.

Real-time image streaming over a low-bandwidth wireless camera network

In this paper we describe the recent development of a low-bandwidth wireless camera sensor network. We propose a simple, yet effective, network architecture which allows multiple cameras to be connected to the network and synchronize their communication schedules. Image compression of greater than 90% is performed at each node running on a local DSP coprocessor, resulting in nodes using 1/8th the energy compared to streaming uncompressed images. We briefly introduce the Fleck wireless node and the DSP/camera sensor, and then outline the network architecture and compression algorithm. The system is able to stream color QVGA images over the network to a base station at up to 2 frames per second. © 2007 IEEE.

More legislative traffic on the 'Doi Moi' superhighway : technology transfer, IP and competition law in Vietnam

Since 1986 Vietnam has been engaged in the transition from a centrally-controlled economy to a socialist-oriented market economy (the 'doi moi' renovation). The process for global economic integration has been slow given the magnitude of necessary reforms. Consequently technology entrepreneurs often discount Vietnam as a possible commercialization base which means that it is not realising its economic potential as a hub of technology transfer in the Asia-Pacific region. Three significant factors in the current uncertainty are Vietnam's laws on competition, intellectual property and technology transfer. Another problem is the lack of literature on these laws. This article first discusses the conceptual relationship between competition, intellectual property and technology transfer. Hopefully the article will provide some guidance for the technology entrepreneur considering foreign direct investment (FDI) in Vietnam. The bottom line is that these laws still need further reform to bolster entrepreneurial confidence.

Cascading appearance-based features for visual voice activity detection

The detection of voice activity is a challenging problem, especially when the level of acoustic noise is high. Most current approaches only utilise the audio signal, making them susceptible to acoustic noise. An obvious approach to overcome this is to use the visual modality. The current state-of-the-art visual feature extraction technique is one that uses a cascade of visual features (i.e. 2D-DCT, feature mean normalisation, interstep LDA). In this paper, we investigate the effectiveness of this technique for the task of visual voice activity detection (VAD), and analyse each stage of the cascade and quantify the relative improvement in performance gained by each successive stage. The experiments were conducted on the CUAVE database and our results highlight that the dynamics of the visual modality can be used to good effect to improve visual voice activity detection performance.

Play a role in the patent puzzle

Discusses the contentious issues surrounding computer software patents and patenting in connection with the Peer-to-Patent Australia project, a joint initiative of Queensland University of Technology (QUT) and New York Law School (NYLS) that operates with the support and endorsement of IP Australia, the government body housing Australia's patent office. Explains that the project is based on the successful Peer-to-Patent pilots run recently in the USA and Japan that are designed to improve the quality of issued patents and the patent examination process by facilitating community participation in that process. Describes how members of the public are allowed to put forward prior art references that will be considered by IP Australia's patent examiners when determining whether participating applications are novel and inventive, and therefore deserving of a patent. Concludes that, while Peer-to-Patent Australia is not a complete solution to the problems besetting patent law, the model has considerable advantages over the traditional model of patent examination

Use of IP addresses for high rate flooding attack detection

High-rate flooding attacks (aka Distributed Denial of Service or DDoS attacks) continue to constitute a pernicious threat within the Internet domain. In this work we demonstrate how using packet source IP addresses coupled with a change-point analysis of the rate of arrival of new IP addresses may be sufficient to detect the onset of a high-rate flooding attack. Importantly, minimizing the number of features to be examined, directly addresses the issue of scalability of the detection process to higher network speeds. Using a proof of concept implementation we have shown how pre-onset IP addresses can be efficiently represented using a bit vector and used to modify a “white list” filter in a firewall as part of the mitigation strategy.