On-line tool condition monitoring and control system in forging processes

Cold bulk metal forming has made large-scale production of small complex solid parts economically feasible. Tooling used in metal forming poses many uncertainties in the preliminary cost estimation and production process and continual tool replacement and maintenance dramatically reduces productivity and raises manufacturing cost. In order to tackle this, an on-line tool condition monitoring system using artificial neural network (ANN) to integrate information from multiple sensors for forging process has been developed. Together with the force, acoustic emission signals and process conditions, information developed from theoretical models is integrated into the ANN tool monitoring system to predict tool life and provide the maintenance schedule.

Decision-making models used by `graduate nurses` managing patients` medications

Background. Nurses in a graduate programme in Australia are those who are in the first year of clinical practice following completion of a 3-year undergraduate nursing degree. When working in an acute care setting, they need to make complex and ever-changing decisions about patients' medications in a clinical environment affected by multifaceted, contextual issues. It is important that comprehensive information about graduate nurses' decision-making processes and the contextual influences affecting these processes are obtained in order to prepare them to meet patients' needs.
Aim. The purpose of this paper is to report a study that sought to answer the following questions: What are the barriers that impede graduate nurses' clinical judgement in their medication management activities? How do contextual issues impact on graduate nurses' medication management activities? The decision-making models considered were: hypothetico-deductive reasoning, pattern recognition and intuition.
Methods. Twelve graduate nurses who were involved in direct patient care in medical and surgical wards of a metropolitan teaching hospital located in Melbourne, Australia participated in the study. Participant observations were conducted with the graduate nurses during a 2-hour period during the times when medications were being administered to patients. Graduate nurses were also interviewed to elicit further information about how they made decisions about patients' medications.
Results. The most common model used was hypothetico-deductive reasoning, followed by pattern recognition and then intuition. The study showed that graduate nurses had a good understanding of how physical assessment affected whether medications should be administered or not. When negotiating treatment options, graduate nurses readily consulted with more experienced nursing colleagues and doctors.
Study limitations. It is possible that graduate nurses demonstrated a raised awareness of managing patients' medications as a consequence of being observed.
Conclusions. The complexity of the clinical practice setting means that graduate nurses need to adapt rapidly to make sound and appropriate decisions about patient care.

Constructing artificial images of facial expressions

This paper presents a method for construction of artificial images of facial expressions. The proposed fractal-based synthesis procedure called pixel-based correspondence works on 2D images and does not require any depth information. This method can generate artificial images of an object when only a single image is given. Using the proposed method, effective example-based facial analysis systems can be trained and utilised in various applications.

Predictive distribution models and their application in wildlife conservation

Wildlife managers are often faced with the difficult task of determining the distribution of species, and their preferred habitats, at large spatial scales. This task is even more challenging when the species of concern is in low abundance and/or the terrain is largely inaccessible. Spatially explicit distribution models, derived from multivariate statistical analyses and implemented in a geographic information system (GIS), can be used to predict the distributions of species and their habitats, thus making them a useful conservation tool. We present two such models: one for a dasyurid, the Swamp Antechinus (Antechinus minimus), and the other for a ground-dwelling bird, the Rufous Bristlebird (Dasyornis broadbenti), both of which are rare species occurring in the coastal heathlands of south-western Victoria. Models were generated using generalized linear modelling (GLM) techniques with species presence or absence as the independent variable and a series of landscape variables derived from GIS layers and high-resolution imagery as the predictors. The most parsimonious model, based on the Akaike Information Criterion, for each species then was extrapolated spatially in a GIS. Probability of species presence was used as an index of habitat suitability. Because habitat fragmentation is thought to be one of the major threats to these species, an assessment of the spatial distribution of suitable habitat across the landscape is vital in prescribing management actions to prevent further habitat fragmentation.

Optimal lag-length choice in stable and unstable VAR models under situations of homoscedasticity and ARCH

The performance of different information criteria - namely Akaike, corrected Akaike (AICC), Schwarz-Bayesian (SBC), and Hannan-Quinn - is investigated so as to choose the optimal lag length in stable and unstable vector autoregressive (VAR) models both when autoregressive conditional heteroscedasticity (ARCH) is present and when it is not. The investigation covers both large and small sample sizes. The Monte Carlo simulation results show that SBC has relatively better performance in lag-choice accuracy in many situations. It is also generally the least sensitive to ARCH regardless of stability or instability of the VAR model, especially in large sample sizes. These appealing properties of SBC make it the optimal criterion for choosing lag length in many situations, especially in the case of financial data, which are usually characterized by occasional periods of high volatility. SBC also has the best forecasting abilities in the majority of situations in which we vary sample size, stability, variance structure (ARCH or not), and forecast horizon (one period or five). frequently, AICC also has good lag-choosing and forecasting properties. However, when ARCH is present, the five-period forecast performance of all criteria in all situations worsens.

Information leakage and informed trading around unscheduled earnings announcements

While there has been much judicial discussion regarding the competency of Australia's continuous disclosure regime with reference to contemporaneous international standards, there has to date been limited empirical analysis of the Australian system's effectiveness in preventing selective disclosure and information leakage. This paper presents an empirical study of information content and trading behaviour around unscheduled earnings announcements - comprising of profit upgrades, profit warnings and neutral trading statements - made by ASX-listed companies during 2004. The contention is that informed trading impacts on the stock returns and trading volumes of listed entities, and hence abnormal returns or trading volumes observed prior to an announcement provide evidence of information leakage. The paper models a range of factors that potentially influence firm disclosure practices and contribute to the level information asymmetry in the market during the pre- announcement period. Previous research has investigated the influence of firm size and information content in contributing to information leakage. This study further considers the variables of firm growth, capital structure and industry group.

Expanding the realm of best practices in cooperative industry-based learning in information systems and information technology : an inter-institutional investigation in Australian higher education

The professional fields of information systems and information technology are drivers and enablers of the global economy. Moreover, their theoretical scope and practices are global in focus. University graduates need to develop a range of leadership, conceptual and technical capacities to work effectively in, and contribute to, the shaping of companies, business models and systems which operate in globalised settings. This paper reports a study of the operation of industry‐based learning (IBL) at three Australian universities, which employ different models and approaches, as part of a series of investigations of the needs, circumstances and perspectives of various stakeholders (program coordinator, faculty teaching staff, the students, industry mentors, and the professional body). The focus of this paper is a discussion of salient pragmatic considerations in an attempt to conceptualize what constitutes best practice in offering industry‐based learning for higher education students in the disciplines of information systems and information technology (Asia‐Pacific Journal of Cooperative Education, 9(2), 73‐80).

Dispersion of information or market behaviour : general public trading in S & P 500 index futures

This paper considers 15 minute records of trading volume and traded prices coinciding with the reporting intervals required by the Commodity Futures Trading Commission. Records are extracted from trade records for two way trade between market makers (CTI1) and the general public (CTI4) from January 1994 to June 2004. Futures price records are matched with S&P500 cash index price records. Simultaneous volatility models are specified and estimated to test trading volume to futures volatility lead/lag effects and also futures volatility to cash index volatility lead/lag effects. There is evidence that existing theoretical models of the general public trading behaviour do not explain such behaviour in these very actively traded markets. These effects can depend more on market conditions than what is suggested in theoretical models.

An artificial neural network-based hairiness prediction model for worsted wool yarns

This study evaluated the performance of multilayer perceptron (MLP) and multivariate linear regression (MLR) models for predicting the hairiness of worsted-spun wool yarns from various top, yarn and processing parameters. The results indicated that the MLP model predicted yarn hairiness more accurately than the MLR model, and should have wide mill specific applications. On the basis of sensitivity analysis, the factors that affected yarn hairiness significantly included yarn twist, ring size, average fiber length (hauteur), fiber diameter and yarn count, with twist having the greatest impact on yarn hairiness.

Conventions of pictorialism (iconic imagery, perceived space and the picture plane) deconstructed and reconstructed as alternative models of perception, embodied in paintings and drawings

This thesis is concerned with conventions of pictorialism, viz. the surface of an artwork or the plane of denotation (in my case paper, canvas or wood); and iconic imagery and the depiction of perceptual space that is connotated by marks, colours and forms upon that surface. Most importantly this thesis is concerned with the relationship between these elements and the deconstruction of them. That the reconstruction of the deconstructed language can create expressive iconic structures that perhaps contain conflicting information and elements, but are simultaneously single and self-contained perceptual models of seeing the world, and the things in it, in another way; is a major focus. The thesis is embodied in the paintings and drawings which are documented in the exegesis that follows.

Beyond the analogon; the "transfer of the referent" : the relationship between the external world experienced through culturally generated perceptual models constructed in the human mind, and the transfer of these images, via visual language, onto referen

Within 20th. Century art, the concept of the ‘normative’ image, as an attribute of things, has been challenged. As a consequence, paintings must now picture the ‘real’ world in other ways, incorporating knowledge and meaning beyond the analogon. Such descriptive representations were revealed as paradigmatic, rather than incontrovertible fact. Dependent on pre-conceived notions of stereotypicality, these descriptive images relied on surface illumination. My thesis explores images of things in the world as culturally inspired and information based. I examine paintings and sculptures of other cultures, such as black African, and other historical periods such as the Medieval, which reveal metonymously the basis for variations in representations of the ‘real’ world. The new enhanced representations which Modern artists created in their work were denigrated as deviant from the absolute ‘normative’ or regarded as distortions for purely mannerist and stylistic reasons. Postmodern research has reassessed them as multiple or extended imagings in whose facture new knowledge and human responses can be incorporated. These new forms of representation can be regarded as theoretical constructs rather than stylised depictions of appearance. In this way referents are transferred through the mind onto objects and vistas in the real world to align with our developed view of the physical world and better our understanding of humanity’s symbiotic relationship with nature.

Physical theory of organisation and consequent neural model of spatio-temporal pattern acquisition

A neurone model (the FORMON) is proposed which provides a mathematical explanation for a range of psychological phenomena and has potential in Artificial Intelligence applications. A general definition of organisation in terms of entropy and information is formulated. The concept of microcodes is introduced to describe the physical nature of organisation. Spatio-temporal pattern acquisition and processing functions attributable to individual neurones are reviewed. The criterion for self-organisation in a neurone is determined as the maximisation of mutual organisation. A feedback control system is proposed to satisfy this criterion and provide an integrated long-term memory of spatio-temporal pattern. This pattern acquisition system is shown to be applicable to dendritic pattern recognition and axonal pattern generation. Provision is also made for adaptation, short-term memory and operant learning. An electro-chemical model of transmission and processing of neural signals is outlined to provide the pattern acquisition functions of the Formon model. A transverse magnetic mode of electrotonic propagation is postulated in addition to the transverse electromagnetic mode. Configurations of the Formon are categorised in terms of possible pattern processing functions. Connective architectures are proposed as self-organising models of acquisitive semantic and syntactic networks.

Modeling intelligent agents for web-based information gathering

The recent emergence of intelligent agent technology and advances in information gathering have been the important steps forward in efficiently managing and using the vast amount of information now available on the Web to make informed decisions. There are, however, still many problems that need to be overcome in the information gathering research arena to enable the delivery of relevant information required by end users. Good decisions cannot be made without sufficient, timely, and correct information. Traditionally it is said that knowledge is power, however, nowadays sufficient, timely, and correct information is power. So gathering relevant information to meet user information needs is the crucial step for making good decisions. The ideal goal of information gathering is to obtain only the information that users need (no more and no less). However, the volume of information available, diversity formats of information, uncertainties of information, and distributed locations of information (e.g. World Wide Web) hinder the process of gathering the right information to meet the user needs. Specifically, two fundamental issues in regard to efficiency of information gathering are mismatch and overload. The mismatch means some information that meets user needs has not been gathered (or missed out), whereas, the overload means some gathered information is not what users need. Traditional information retrieval has been developed well in the past twenty years. The introduction of the Web has changed people's perceptions of information retrieval. Usually, the task of information retrieval is considered to have the function of leading the user to those documents that are relevant to his/her information needs. The similar function in information retrieval is to filter out the irrelevant documents (or called information filtering). Research into traditional information retrieval has provided many retrieval models and techniques to represent documents and queries. Nowadays, information is becoming highly distributed, and increasingly difficult to gather. On the other hand, people have found a lot of uncertainties that are contained in the user information needs. These motivate the need for research in agent-based information gathering. Agent-based information systems arise at this moment. In these kinds of systems, intelligent agents will get commitments from their users and act on the users behalf to gather the required information. They can easily retrieve the relevant information from highly distributed uncertain environments because of their merits of intelligent, autonomy and distribution. The current research for agent-based information gathering systems is divided into single agent gathering systems, and multi-agent gathering systems. In both research areas, there are still open problems to be solved so that agent-based information gathering systems can retrieve the uncertain information more effectively from the highly distributed environments. The aim of this thesis is to research the theoretical framework for intelligent agents to gather information from the Web. This research integrates the areas of information retrieval and intelligent agents. The specific research areas in this thesis are the development of an information filtering model for single agent systems, and the development of a dynamic belief model for information fusion for multi-agent systems. The research results are also supported by the construction of real information gathering agents (e.g., Job Agent) for the Internet to help users to gather useful information stored in Web sites. In such a framework, information gathering agents have abilities to describe (or learn) the user information needs, and act like users to retrieve, filter, and/or fuse the information. A rough set based information filtering model is developed to address the problem of overload. The new approach allows users to describe their information needs on user concept spaces rather than on document spaces, and it views a user information need as a rough set over the document space. The rough set decision theory is used to classify new documents into three regions: positive region, boundary region, and negative region. Two experiments are presented to verify this model, and it shows that the rough set based model provides an efficient approach to the overload problem. In this research, a dynamic belief model for information fusion in multi-agent environments is also developed. This model has a polynomial time complexity, and it has been proven that the fusion results are belief (mass) functions. By using this model, a collection fusion algorithm for information gathering agents is presented. The difficult problem for this research is the case where collections may be used by more than one agent. This algorithm, however, uses the technique of cooperation between agents, and provides a solution for this difficult problem in distributed information retrieval systems. This thesis presents the solutions to the theoretical problems in agent-based information gathering systems, including information filtering models, agent belief modeling, and collection fusions. It also presents solutions to some of the technical problems in agent-based information systems, such as document classification, the architecture for agent-based information gathering systems, and the decision in multiple agent environments. Such kinds of information gathering agents will gather relevant information from highly distributed uncertain environments.

Helping teachers surf the information and communication technology tsunami

A range of factors, both internal and external, is creating changes in teaching and teachers’ professional lives. Information and Communication Technology (ICT) is just one of the major changes impacting on the teaching profession. As teachers face intense pressure to adapt to this tsunami, this study aims to investigate ways in which teachers can be helped. In South Australia, where this study is set, all teachers in Government schools are expected to be "ICT Smart", i.e. able to use appropriate forms of ICT to enhance the teaching and learning environment of their classrooms. From the researcher’s involvement for over a decade in professional development for teachers, and from visits to many schools, it appears that numerous teachers have not reached this standard. The greatest need is in Reception to Year 7 schools where the average age of teachers is nearly 50. Because no state-wide data exists, this study is intended to establish if there is a problem and if there is, to identify specific needs and offer possible solutions. The study is comprised of four parts: Part A, the Introduction gives an overview of the inter-relationships between these parts and the overall Folio. It establishes the setting and provides a rationale for the study and its focus on Professional Development in Information and Communication Technology. Part B, the Elective Research Studies, follows the writer’s involvement in this field since the 1980s. It establishes the theme of "Moving best practice in ICT from the few to the many" which underlies the whole study. Part C, the Dissertation, traces the steps taken to investigate the need for professional development in ICT. This is achieved by analysing and commenting on data collected from a state-wide survey and a series of interviews with leading figures, and by providing a review of the relevant literature and past and existing models of professional development. Part D, Final Comments, provides an overview of the whole Folio and a reflection on the research that has been conducted. The findings are that there is widespread dissatisfaction with existing models and that there is an urgent need for professional development in this area, because nearly 20% of teachers either do not use computers or are considered to be novice users. Another 25% are considered to be below not yet "ICT Smart". Less than 10% of ICT co-ordinators have a formal qualification in the field but more than 85% of them are interested in a Masters program. The study offers solutions in Part B where there is a discussion of a range of strategies to provide on-going professional development for teachers. Chapter 9 provides an outline of a proposed Masters level program and offers suggestions on how it could be best delivered. This program would meet the identified needs of ICT co-ordinators. The study concludes with a series of recommendations and suggestions for further research. The Education Department must address these urgent professional development needs of teachers, particularly those in the more remote country regions. There needs to be a follow-up survey to establish to what extent teachers in South Australia are now "ICT Smart ".

Design and degradation modelling through artificial neural networks

Automotive is one of the major manufacturing industries in Australia that requires extensive reliability test for the components used in vehicles. To achieve a shorter time-to-market and a highly reliable product while reducing the amount of physical prototyping, there is a growing need for better understanding on the effect that the design parameters have on the degradation of the product. This paper presents comprehensive descriptions of applying Artificial Neural Network (ANN) to capture the relationships between design and degradation. Consequently, two models of different practical significance are created as the result of the work. The vision of the models is to be used by the testers and designers as a guideline in design evaluation, so that time-consuming and expensive iterations of the product developmental cycle can be reduced substantially. The degradation of the folding force of a mechanical system is used to illustrate our approach.