Why fundamentalism?

Why Fundamentalism? was an exhibition proposal and critical writing project developed from concept phase through to detailed proposal. It included an edited video document that lay out its core ideas and presented the diverse voices of each collaborator. A number of key themes were engaged around the hot-button (and much misunderstood) concept of Fundamentalism. The proposal included an exhibition layout, developed test imagery, ideas and animations, proposed forms for future works and a process whereby design briefs would lead to subsequent commissions. Two major grant applications were submitted to the Australia Council and Arts Queensland, with the support of State Library of Queensland, the University of Adelaide and numerous others. The project remains at the developed proposal stage awaiting suitable funding----- Critically the show became an active vehicle for drawing and exploring a line of distinction between ideas of ‘what is fundamental’ and ‘fundamentalism’ as it rested in the popular imagination, as well as in political and philosophical debates. It teased out and engaged with a number of key questions that included The Problem of Ungroundedness, A Politics of Finitude, The Post-modern/Pluralist Problem, Silent Fundamentalisms (Voices of Reason and Neo-con Religions), Fundamentalism as a Media Construct, The Pre and Post Cold-war Other, The Pressing Need for Foundations in the West and Islam as Foundationalism (rather than fundamentalism).

PhD forum : multiple camera management using wide base-line matching

Manual calibration of large and dynamic networks of cameras is labour intensive and time consuming. This is a strong motivator for the development of automatic calibration methods. Automatic calibration relies on the ability to find correspondences between multiple views of the same scene. If the cameras are sparsely placed, this can be a very difficult task. This PhD project focuses on the further development of uncalibrated wide baseline matching techniques.

An institutional understanding of triple bottom line evaluations and the use of social and environmental metrics

Measuring social and environmental metrics of property is necessary for meaningful triple bottom line (TBL) assessments. This paper demonstrates how relevant indicators derived from environmental rating systems provide for reasonably straightforward collations of performance scores that support adjustments based on a sliding scale. It also highlights the absence of a corresponding consensus of important social metrics representing the third leg of the TBL tripod. Assessing TBL may be unavoidably imprecise, but if valuers and managers continue to ignore TBL concerns, their assessments may soon be less relevant given the emerging institutional milieu informing and reflecting business practices and society expectations.

Catalogue essay : a thin white line

Objects have consequences, seemingly. They move, atomic, formlessly – when static they are seen. That they vibrate constantly, that they are NOW present, is something we will have to trust the physicists on. They only seem here. Now is their moment of form, but later, who knows? Things SEEM when we recognise our own transience and temporary-ness. We call upon a bevy of senses that forever frustrate us with their limitation, despite our little understanding of what we actually have – is this here? So some forms seem to be telling us to trust our senses – that this world IS as it seems. Their form constantly refines and is refined and refined until in its essentialness it cannot be doubted – it absolutely IS. Is this our eyes? Can we only see it? But light is also a particle, if I remember correctly, so there is some weight to seeing. So to SEEM is also to FEEL,as this light imposes its visual weight upon our skins – we see with every pore of our body.

Urban network travel time estimation from stop-line loop detector data and signal controller data

This paper presents a model to estimate travel time using cumulative plots. Three different cases considered are i) case-Det, for only detector data; ii) case-DetSig, for detector data and signal controller data and iii) case-DetSigSFR: for detector data, signal controller data and saturation flow rate. The performance of the model for different detection intervals is evaluated. It is observed that detection interval is not critical if signal timings are available. Comparable accuracy can be obtained from larger detection interval with signal timings or from shorter detection interval without signal timings. The performance for case-DetSig and for case-DetSigSFR is consistent with accuracy generally more than 95% whereas, case-Det is highly sensitive to the signal phases in the detection interval and its performance is uncertain if detection interval is integral multiple of signal cycles.

Optimal allocation and sizing of capacitors to minimize the transmission line loss and to improve the voltage profile

To allocate and size capacitors in a distribution system, an optimization algorithm, called Discrete Particle Swarm Optimization (DPSO), is employed in this paper. The objective is to minimize the transmission line loss cost plus capacitors cost. During the optimization procedure, the bus voltage, the feeder current and the reactive power flowing back to the source side should be maintained within standard levels. To validate the proposed method, the semi-urban distribution system that is connected to bus 2 of the Roy Billinton Test System (RBTS) is used. This 37-bus distribution system has 22 loads being located in the secondary side of a distribution substation (33/11 kV). Reducing the transmission line loss in a standard system, in which the transmission line loss consists of only about 6.6 percent of total power, the capabilities of the proposed technique are seen to be validated.

Towards automatic power line detection for a UAV surveillance system using pulse coupled neural filter and an improved Hough transform

Spatial information captured from optical remote sensors on board unmanned aerial vehicles (UAVs) has great potential in automatic surveillance of electrical infrastructure. For an automatic vision-based power line inspection system, detecting power lines from a cluttered background is one of the most important and challenging tasks. In this paper, a novel method is proposed, specifically for power line detection from aerial images. A pulse coupled neural filter is developed to remove background noise and generate an edge map prior to the Hough transform being employed to detect straight lines. An improved Hough transform is used by performing knowledge-based line clustering in Hough space to refine the detection results. The experiment on real image data captured from a UAV platform demonstrates that the proposed approach is effective for automatic power line detection.