Modelling regular and estimable inverse demand systems : a distance function approach

To be useful for policy simulation in the current climate of rapid structural change, inverse demand systems must remain regular over substanstial variations in quantities. The distance function is a convenient vehicle for generating such systems. It also allows convenient imposition of prior ideas about the structure of preferences required for realistic policy work. While the distance function directly yields Hicksian inverse demand functions via the Shepard-Hanoch lemma, they are usually explicit in the unobservable level of utility (u), but lack a closed-form representation in terms of the observable variables. Note however that the unobservability of u need not hinder estimation. A simple one-dimensional numerical inversion allows the estimation of the distance function via the parameters of the implied Marshallian inverse demand functions. This paper develops the formal theory for using distance functions in this context, and reports on initial trials on the operational feasibility of the method.

Using geometric shape variations to create an inverse model for a sheet metal process

The output of the sheet metal forming process is subject to much variation. This paper develops a method to measure shape variation in channel forming and relate this back to the corresponding process parameter levels of the manufacturing set-up to create an inverse model. The shape variation in the channels is measured using a modified form of the point distribution model (also known as the active shape model). This means that channels can be represented by a weighting vector of minimal linear dimension that contains all the shape variation information from the average formed channel.

The inverse models were created using classifiers that related the weighting vectors to the process parameter levels for the blank holder force (BHF), die radii (DR) and tool gap (TG) of the parameters. Several classifiers were tested: linear, quadratic Gaussian and artificial neural networks. The quadratic Gaussian classifiers were the most accurate and the most consistent type of classifier over all the parameters.

Enhancing the learning environment for distance education students

This paper reports on the development of an asynchronous learning  environment for the teaching of introductory macroeconomics to    approximately 200 distance education students. The research supports evidence in the current literature that computer mediated communication and in particular, collaborative learning, can make a positive difference to the educational experience of some students. These findings are based on both quantitative and qualitative data gained from student evaluations,  participation levels, staff interviews and an analysis of the online communication. The discussion centres on the extent of collaboration, the role of assessment, adaptation of curriculum and pedagogy and the students' attitudes to economics.

The influence of time since fire and distance from fire boundary on the distribution and abundance of arboreal marsupials in Eucalyptus regnans-dominated forest in the Central Highlands of Victoria

The impact of time since fire after two consecutive wildfires 44 years apart (1939 and 1983) within the same area, and the distance from the fire boundary «100 m or 500-2000 m), were investigated in relation to the distribution and abundance of arboreal marsupials in 1994. Arboreal marsupials were censused by stagwatching and spotlighting in two relatively young age classes of mountain ash (Eucalyptus regnans) dominated forest in the Central Highlands of Victoria. Five species of arboreal marsupial were detected, but only three were detected in sufficient numbers to determine habitat preferences. Petauroides volans (greater glider) was statistically more abundant in 1939 regrowth forests, while Trichosurus caninus (mountain brushtail possum) showed no significant preference for either age class of forest. All but one record of Gymnobelideus leadbeateri (Leadbeater's possum) came from young forest, though the effect of age-class was not statistically significant. Distance from fire boundary explained little or no variation in mammal distribution or abundance. While the actual number of hollow-bearing trees was similar in both age classes of forest, the long-term lifespan of hollow-bearing trees in more recently burnt forest is predicted to be lower than in unburnt or not recently burnt forest. Post-fire salvage logging following the 1983 wildfires appears to have reduced the number of hollow-bearing trees at sites burnt in 1983.

Social presence online: networking learners at a distance

This paper draws on two studies which researched the use of online small group environments where collaborative learning is a central structure for learning. The establishment of social presence is facilitated through the socio-affective aspect of small group interaction which contributed to the effectiveness of learning online. Social presence, the ability of online learners to project themselves into a textual environment which has few visual or contextual cues, will be explored as an important element in facilitating effective online learning. The teacher's role in helping students project their online social presence and in establishing an environment for learning within the larger group computer conference will also be discussed.

Distance learning for laboratory practical work in microcontrollers

This paper presents a simple and relatively straightforward solution to the problems of equity in laboratory practical exposure between distance-education students and their traditional, on-campus, fellow cohort. This system has been implemented for the past five years in a university that is amongst the leaders in distance education delivery and has proved to be extremely successful and very well accepted by all students. While the intention was to allow distance education students easy access to the required laboratory practical content of the course, the solution found has proved to have many advantages for the on-campus students. Although this specific implementation is based upon microcontroller technology units in an engineering degree course, the methodology is easily transferable to other disciplines and courses.

A grid-based index method for time warping distance

Recently DTW (dynamic time warping) has been recognized as the most robust distance function to measure the similarity between two time series, and this fact has spawned a flurry of research on this topic. Most indexing methods proposed for DTW are based on the R-tree structure. Because of high dimensionality and loose lower bounds for time warping distance, the pruning power of these tree structures are quite weak, resulting in inefficient search. In this paper, we propose a dimensionality reduction method motivated by observations about the inherent character of each time series. A very compact index file is constructed. By scanning the index file, we can get a very small candidate set, so that the number of page access is dramatically reduced. We demonstrate the effectiveness of our approach on real and synthetic datasets.

The history of distance education in Australia

This article presents a history of distance education in Australia. Australia's large distances and widely distributed population has meant that distance education has been an important part of its history. From the earliest provision of schooling by mail through a series of correspondence schools, both state and federal governments have provided a sound infrastructure to support distance education. Innovative uses of technologies to provide communication and interaction and ease the isolation of distance have also been a feature of Australia's distance education history. The impact of this history is particularly relevant as the Internet and information and communication technologies are changing this field and making distance educators of all institutions and sectors.

Geometric shape errors in forging: developing a metric and an inverse model

The complexity of the forging process ensures that there is inherent variability in the geometric shape of a forged part. While knowledge of shape error, comparing the desired versus the measured shape, is significant in measuring part quality the question of more interest is what can this error suggest about the forging process set-up? The first contribution of this paper is to develop a shape error metric which identifies geometric shape differences that occur from a desired forged part. This metric is based on the point distribution deformable model developed in pattern recognition research. The second contribution of this paper is to propose an inverse model that identifies changes in process set-up parameter values by analysing the proposed shape error metric. The metric and inverse models are developed using two sets of simulated hot-forged parts created using two different die pairs (simple and 'M'-shaped die pairs). A neural network is used to classify the shape data into three arbitrarily chosen levels for each parameter and it is accurate to at least 77 per cent in the worst case for the simple die pair data and has an average accuracy of approximately 80 per cent when classifying the more complex 'M'-shaped die pair data.