We need one district government to be set up to replace other district governments : the beginnings of Provincial Government in Papua New Guinea

Decentralisation, provincial government, and regional autonomy continue as influential factors in Papua New Guinea’s political economy.  The role played in creating PNG’s provincial government system by separatist movements in East New Britain, Bougainville and elsewhere is acknowledged.  However, as the Constitutional Planning Committee (CPC) discovered during its program of consultations with the Papua New Guinean people from 1972 to 1974, there was a strong groundswell around the country for district-level governments.  This article investigates how the CPC stimulated discussion of this issue through its own activities, and how the people in their discussion groups responded to the CPC’s ‘Discussion Paper on Relations Between the Central Government and Other Levels of Government’.

Adolescent parenthood : a costly mistake or a search for love?

Family life is changing worldwide and an increasing number of women are choosing single parenthood. Adolescents who become pregnant and early childbearers do not always become pregnant unintentionally; some actively plan pregnancy while others are ambivalent mainly about the timing. This paper reports on a study using an ethnographic approach that explored the mothering experiences of five sole-supporting Australian teenage mothers who had a child over six months of age. It focuses on the story of one of them, a young woman who gave birth at 16 and set up home for herself and her son. Early childbearing is often a response to adverse social conditions such as poverty or homelessness and is not uncommonly chosen by teenage girls from socially deprived backgrounds. Educational and employment opportunities may be limited, whilst motherhood may provide a purpose in life when few other options are possible. Young women who make this choice need comprehensive services to support them in the parenting role, including appropriate health care, welfare and housing benefits, and support in dealing with parenting, a role which they may greatly desire but are not automatically well prepared for.

Corporate liability for workplace deaths and injuries-reflecting on Victoria's laws in the light of the Esso Longford explosion

The purpose of this article is to consider some different legal models for the liability of corporations for the deaths and serious injuries of their employees, with particular emphasis on the law in Victoria.

Two recent developments in Victoria prompt this consideration. First, on 30 July 2001, the Victorian Supreme Court handed down its sentencing decision in the case arising from the explosion on 25 September 1998 at the Longford gas plant operated by Esso Australia Pty Ltd. The decision marked the end of the formal public consideration of a devastating event in Victorian industrial history, which began with the Royal Commission set up on 20 October 1998 to investigate the causes of an explosion in which two workers died and eight others were injured. Second, in early 2002, the Victorian Government failed in its attempt to introduce new criminal offences for corporate employers whose employees are killed or seriously injured at work. In spite of their failure to be passed by the Legislative Council in Victoria, these proposals warrant consideration. They represent a growing trend by policy makers in attempting to address more effectively the question of the liability for deaths and serious injuries of workers to employers who operate through the corporate form.

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.

Force modelling of the crankshaft pin grinding process.

A force model was developed for crankshaft pin grinding to predict the forces generated during grinding. The force model developed builds on the authors’ previously developed model, which predicted the out-of-roundness in crankshaft pin grinding. The model includes key grinding variables, such as the work removal parameter (WRP), system sti€ ness and Young’s modulus to determine the end forces produced. The model also includes the important geometrical relationships that are unique to this type of grinding. The model was veriŽ ed using an experiential set-up involving sophisticated strain gauge force measurements on a commercial Landis CP grinding machine, with close correlation between the results and the model.

Criminal penalties for contraventions of Part IV of the Trade Practices Act

In 2003 the Dawson Committee, commissioned by the Government, recommended that criminal penalties should be introduced for cartel conduct. The Government accepted this recommendation in principle and set up a working party to consider the implementation difficulties that had been identified in the Dawson Report. Nothing further was heard from the Government until February 2005 when the Government announced that it would introduce criminal penalties for serious cartel conduct. This paper evaluates the Government proposals and makes suggestions for their implementation.

Photocatalytic reduction of carbon dioxide into gaseous hydrocarbon using TiO2 pellets

It has been shown that CO₂ could be transformed into hydrocarbons when it is in contact with water vapour and catalysts under UV irradiation. This paper presents an experimental set-up to study the process employing a new approach of heterogeneous photocatalysis using pellet form of catalyst instead of immobilized catalysts on solid substrates. In the experiment, CO₂ mixed with water vapour in saturation state was discharged into a quartz reactor containing porous TiO₂ pellets and illuminated by various UV lamps of different wavelengths for 48 h continuously. The gaseous products extracted were identified using gas chromatography. The results confirmed that CO₂ could be reformed in the presence of water vapour and TiO₂ pellets into CH₄ under continuous UV irradiation at room conditions. It showed that when UVC (253.7 nm) light was used, total yield of methane was approximately 200 ppm which was a fairly good reduction yield as compared to those obtained from the processes using immobilized catalysts through thin-film technique and anchoring method. CO and H₂ were also detected. Switching from UVC to UVA (365 nm) resulted in significant decrease in the product yields. The pellet form of catalyst has been found to be attractive for use in further research on photocatalytic reduction of CO₂.

Finite element modelling of metallic tubular crash structures with an explicit code

Numerous experimental studies have been carried out to investigate the collapse of tubular metallic crash structures under axial compression. Some simple theoretical models have been developed but these often assume one type of progressive collapse, which is not always representative of the real situation. Finite Element (FE) models, when further refined, have the potential to predict the actual collapse mode and how it influences the load-displacement and energy absorption characteristics. This paper describes an FE modelling investigation with the explicit code LS−DYNA. An automatic mesh generation programme written by the authors is used to set up shell and solid element tube models. Mesh specification issues and features relating to the contact and friction models are discussed in detail. The crush modes, load-deflection characteristics and energy absorption values found in the simulations are compared with a reasonable degree of correlation to those observed in a physical testing programme; however, improvements are still required.

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.

Improving an inverse model of sheet metal forming by neural network based regression

An inverse model for a sheet meta l forming process aims to determine the initial parameter levels required to form the final formed shape. This is a difficult problem that is usually approached by traditional methods such as finite element analysis. Formulating the problem as a classification problem makes it possible to use well established classification algorithms, such as decision trees. Classification is, however, generally based on a winner-takes-all approach when associating the output value with the corresponding class. On the other hand, when formulating the problem as a regression task, all the output values are combined to produce the corresponding class value. For a multi-class problem, this may result in very different associations compared with classification between the output of the model and the corresponding class. Such formulation makes it possible to use well known regression algorithms, such as neural networks. In this paper, we develop a neural network based inverse model of a sheet forming process, and compare its performance with that of a linear model. Both models are used in two modes, classification mode and a function estimation mode, to investigate the advantage of re-formulating the problem as a function estimation. This results in large improvements in the recognition rate of set-up parameters of a sheet metal forming process for both models, with a neural network model achieving much more accurate parameter recognition than a linear model.

The application of ant colony systems to image texture classification

This paper presents a novel ant system based optimisation method which integrates genetic algorithms and simplex algorithms. This method is able to not only speed up the search process for solutions, but also improve the quality of the solutions. In this paper, the proposed method is applied to set up a learning model for the "tuned" mask, which is used for texture classification. Experimental results on aerial images and comparisons with genetic algorithms and genetic simplex algorithms are presented to illustrate the merit and feasibility of the proposed method.

Concepts, models and analyses of electronic demolition of buildings

The demolition of building structures produces enormous amounts of waste materials. In most current demolition projects, a great number of demolished materials are directly sent to landfill after their primary usage due to the difficulties in finding their next usage immediately. At the same time, because of limited supply of second-hand materials, new and high quality materials are used in construction projects whose design standards can be fitted using the secondary or used materials. However, this is an inefficient method to reduce waste because off the flow nature of the current waste-exchange systems and the demolition procedure. The recent concept using deconstruction rather than destruction for demolishing a constructed facility fails to achieve widespread understanding or acceptance due to various practical limitations. In this paper, for the purpose of envisaging the deconstruction implementations in practice and promoting cascading usages of construction materials, the concept of electronic demolition (e-Demotion, eDemolition) is put forward for the first time. E-demolition is a virtual demolition approach by which the demolition information, progress and outputs are operated before the physical demolition. Furthermore, the authors set up the essential models to implement electronic demolition of buildings from the viewpoints of demolition progress, business, and information. Each model is demonstrated in accord with the conventional demolition practice and subject to the ideal deconstruction implementation. Following the electronic demolition of a real project, the physical demolition can be anticipated with a minimum of construction waste emission.

Hybrid ant colony algorithm for texture classification

We present a novel ant colony algorithm integrating genetic algorithms and simplex algorithms. This method is able to not only speed up searching process for optimal solutions, but also improve the quality of the solutions. The proposed method is applied to set up a learning model for the "tuned" mask, which is used for texture classification. Experimental results on real world images and comparisons with genetic algorithms and genetic simplex algorithms are presented to illustrate the merit and feasibility of the proposed method.

Modelling the diffuse fraction of global solar radiation on a horizontal surface

For various applications it is necessary to know not only global solar radiation values, but also the diffuse and beam components. Because often only global values are available, there have been several models developed to establish correlations between the diffuse fraction and various predictors. These typically include the clearness index, but also may include the solar angle, temperature and humidity. The clearness index is the proportion of extraterrestrial radiation reaching a location, where the extraterrestrial value used in the calculation varies with latitude and time of year. These correlations have been developed using data principally from latitudes greater than 40°, often using only data from a few locations and with few exceptions have not used solar altitude as a predictor. Generally the data consist of hourly integrated values. A model has been developed using hourly data from a weather station set up at Deakin University, Geelong. Another model has also been developed for 15 minute data values in order to ascertain if the smoothing generated by using hourly data makes a significant difference to overall results. The construction of such models has been investigated, enabling an extension to the research, inclusive of other stations, to be performed systematically. A final investigation was carried out, using data from other Australian locations, to explain some of the considerable scatter by adding apparent solar time as a predictor, which proved to be significantly better than solar altitude.