Enlistment and non-enlistment in wartime Australia : responses to the 1916 call to arms appeal

This article examines men’s responses to the 1916 ‘Call to Arms’ appeal, in which Australia’s federal government questioned military-aged male citizens on their willingness to enlist voluntarily in the armed forces for service at the front. It argues that the appeal illuminated men’s difficult negotiation of choice, in which they weighed their personal sense of obligation to the state at war, to their families, and to themselves. It shows how men not only confronted their decision, but measured their responsibilities against others’, producing a subjective order of sacrifice that paralysed recruiting. In the absence of conscription, that private decision-making was critical to the nature of Australia’s commitment to the war, as men assessed and re-assessed the limits of obligation for themselves.

Why has the rising economic tide failed to float the disability employment boat? A call to action : business,community, government and people power

It is well established that people with disabilities are under-represented in the workforce. Disability labour market scholars agree that there is a significant gap between labour market participation of people with disabilities and people without disabilities, with on-going labour market disadvantage widely reported. All indicate that notwithstanding the recent economic growth of Western economies, the employment rate for people with disabilities has not improved. This paper draws on the findings of three recent research projects on disability employment in Australia and on data from contemporary literature on workplace discrimination and proposes that a combination of more robust social inclusion policies and legislation, revitalised supported employment models, intensive social marketing, and radical disability advocacy is required.

Call for research – the consuming child-in-context in unhealthy and unsustainable times

Childhood obesity is a highly complex issue with serious health and environmental implications. It has been postulated that young children (preschool-aged in particular) are able to internalise positive environmental beliefs. Applying a socioecological theoretical perspective, in this discussion paper we argue that although children may internalise such beliefs, they commonly behave in ways that contradict these beliefs as demonstrated by their consumer choices. The media directly influences these consumer choices and growing evidence suggests that media exposure (particularly commercial television viewing) may be a significant “player” in the prediction of childhood obesity. However, there is still debate as to whether childhood obesity is caused by digital media use per se or whether other factors mediate this relationship. Growing evidence suggests that researchers should examine whether different types of content have conflicting influences on a child’s consumer choices and, by extension, obesity. The extent to which young children connect their consumer choices and the sustainability of the product/s they consume with their overall health and wellbeing has not previously been researched. To these ends, we call for further research on this socioecological phenomenon among young children, particularly with respect to the influence of digital media use on a child’s consumer behaviours.

Academics call for review of school religious teaching

Religious education in state schools must be replaced by a multifaith version that includes different ethical traditions and be taught by trained teachers rather than volunteers, says a new network of academics.

Zero-day malware detection based on supervised learning algorithms of API call signatures

Zero-day or unknown malware are created using code obfuscation techniques that can modify the parent code to produce offspring copies which have the same functionality but with different signatures. Current techniques reported in literature lack the capability of detecting zero-day malware with the required accuracy and efficiency. In this paper, we have proposed and evaluated a novel method of employing several data mining techniques to detect and classify zero-day malware with high levels of accuracy and efficiency based on the frequency of Windows API calls. This paper describes the methodology employed for the collection of large data sets to train the classifiers, and analyses the performance results of the various data mining algorithms adopted for the study using a fully automated tool developed in this research to conduct the various experimental investigations and evaluation. Through the performance results of these algorithms from our experimental analysis, we are able to evaluate and discuss the advantages of one data mining algorithm over the other for accurately detecting zero-day malware successfully. The data mining framework employed in this research learns through analysing the behavior of existing malicious and benign codes in large datasets. We have employed robust classifiers, namely Naïve Bayes (NB) Algorithm, k−Nearest Neighbor (kNN) Algorithm, Sequential Minimal Optimization (SMO) Algorithm with 4 differents kernels (SMO - Normalized PolyKernel, SMO – PolyKernel, SMO – Puk, and SMO- Radial Basis Function (RBF)), Backpropagation Neural Networks Algorithm, and J48 decision tree and have evaluated their performance. Overall, the automated data mining system implemented for this study has achieved high true positive (TP) rate of more than 98.5%, and low false positive (FP) rate of less than 0.025, which has not been achieved in literature so far. This is much higher than the required commercial acceptance level indicating that our novel technique is a major leap forward in detecting zero-day malware. This paper also offers future directions for researchers in exploring different aspects of obfuscations that are affecting the IT world today.