Visions of the virtual : the role of computers and artificial intelligence in a selection of Australian young adult fiction

Advances in computer technology over the last twenty years have resulted in a number of different visions of what it means to be real, and of what it means to be human. This paper will explore how computers and artificial intelligence are used as major themes in four Australian novels written for young adults: Gillian Rubinstein’s Space Demons trilogy — comprising Space Demons, Skymaze and Shinkei — and Michael Pryor’s The Mask of Caliban. In so doing, the paper will look at how these texts explore the relationship between increasingly developed technology and visions of a better world. By comparing a series of oppositions that occur in all four books, this paper will look at how the theme of technology is used to privilege particular values and to advocate particular beliefs.

Is proof dead in the age of computers?

Some knowledge of what it means to construct a proof is an extremely important part of mathematics. All mathematics teachers and students should have some exposure to the ideas of proof and proving. This paper deals with the issue of creating proofs in mathematics problems.

Laptop computers as a mediating tool between teacher beliefs and pedagogy

This study focused on teachers of senior secondary classes and the impact on pedagogy of the use of laptop computers. It was found that in schools operating a mature laptop program, pedagogy was influenced by teacher beliefs, prevailing school culture, and the assessment requirements of students in their final year.

Self-taught approach to teaching with computers : a case study

The study has investigated the pedagogy of teachers with litle or no training in computer use. The value of a self-taught approach to teacher learning about teaching with computers was scrutinised, and a range of practical implications for the professional development of such teachers was identified.

Computers for secondary mathematics: who uses them and how?

In the first stage of a three year ARC-funded study in which the effects of using computers for the teaching and learning of mathematics are being explored, a questionnaire has been developed and is being administered to a large number of students in grades 7-10 in a representative sample of co-educational post-primary schools in Victoria. Using open and closed response formats, the information sought includes: background and biographical details; data on computer ownership and use =96 frequency and mode/s =96 for mathematics learning at home and in mathematics classes; and beliefs about mathematics and the use of computers for learning mathematics. In this paper, the focus will be on some of the preliminary findings related to ownership and use of computers for learning mathematics at home and at school. In previous research, factors such as gender, socio-economic background, and ethnicity have been identified as contributors to inequitable mathematics learning outcomes. The questionnaire data will be analysed to examine if these and other factors are related to any inequities identified in student's access to computers and in how they use computers in their learning of mathematics. The results will be presented and pertinent implications discussed.

Candidate working set strategy based SMO algorithm in support vector machine

Sequential minimal optimization (SMO) is quite an efficient algorithm for training the support vector machine. The most important step of this algorithm is the selection of the working set, which greatly affects the training speed. The feasible direction strategy for the working set selection can decrease the objective function, however, may augment to the total calculation for selecting the working set in each of the iteration. In this paper, a new candidate working set (CWS) Strategy is presented considering the cost on the working set selection and cache performance. This new strategy can select several greatest violating samples from Cache as the iterative working sets for the next several optimizing steps, which can improve the efficiency of the kernel cache usage and reduce the computational cost related to the working set selection. The results of the theory analysis and experiments demonstrate that the proposed method can reduce the training time, especially on the large-scale datasets.

Prediction of wool knitwear pilling propensity using support vector machines

The propensity of wool knitwear to form entangled fiber balls, known as pills, on the surface is affected by a large number of factors. This study examines, for the first time, the application of the support vector machine (SVM) data mining tool to the pilling propensity prediction of wool knitwear. The results indicate that by using the binary classification method and the radial basis function (RBF) kernel function, the SVM is able to give high pilling propensity prediction accuracy for wool knitwear without data over-fitting. The study also found that the number of records available for each pill rating greatly affects the learning and prediction capability of SVM models.

Boron nitride nanotubes : a novel vector for targeted magnetic drug delivery

Whereas several biomedical applications of carbon nanotubes have been proposed, the use of boron nitride nanotubes (BNNTs) in this field has been largely unexplored despite their unique and potentially useful properties. Our group has recently initiated an experimental program aimed at the exploration of the interactions between BNNTs and living cells. In the present paper, we report on the magnetic properties of BNNTs containing Fe catalysts which confirm the feasibility for their use as nanovectors for targeted drug delivery. The magnetisation curves of BNNTs characterised by the present study are typical of superparamagnetic materials with important parameters, including magnetic permeability and magnetic momentum, derived by employing Langevin theory. In-vitro tests have demonstrated the feasibility for influencing the uptake of BNNTs by living cells by exposure to an external magnetic source. A finite element method analysis devised to predict this effect produced predictive data with close agreement with the experimental observations.

Democratic deliberation, citizenship, and networked computers

This study offers a multi-faceted response to the question of whether or not network computers can improve citizen power from the perspective of deliberative democratic theory. It concludes that in particular circumstances, computers can enhance citizens' power, and improve deliberation in liberal-democratic forums.

A multi-vector, multi-envelope HIV-1 vaccine

The St. Jude Children's Research Hospital (St. Jude) HIV-1 vaccine program is based on the observation that multiple, antigenically distinct HIV-1 envelope protein structures are capable of mediating HIV-1 infection. A cocktail vaccine comprising representatives of these diverse structures (immunotypes) is therefore considered necessary to elicit lymphocyte populations that prevent HIV-1 infection. This strategy is reminiscent of that used to design a currently licensed and successful 23-valent pneumococcus vaccine. Three recombinant vector systems are used for the delivery of envelope cocktails (DNA, vaccinia virus, and purified protein) and each of these has been tested individually in phase I safety trials. A fourth clinical trial, in which diverse envelopes and vectors are combined in a prime-boost vaccination regimen, has been FDA-approved and is expected to commence in 2007. This trial will continue to test the hypothesis that a multivector, multi-envelope vaccine can elicit diverse 8- and T-cell populations that can prevent HIV-1 infections in humans.