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.

Energy-efficient management of data center resources for cloud computing : a vision, architectural elements, and open challenges

Cloud computing is offering utility-oriented IT services to users worldwide. Based on a pay-as-you-go model, it enables hosting of pervasive applications from consumer, scientific, and business domains. However, data centers hosting Cloud applications consume huge amounts of energy, contributing to high operational costs and carbon footprints to the environment. Therefore, we need Green Cloud computing solutions that can not only save energy for the environment but also reduce operational costs. This paper presents vision, challenges, and architectural elements for energy-efficient management of Cloud computing environments. We focus on the development of dynamic resource provisioning and allocation algorithms that consider the synergy between various data center infrastructures (i.e., the hardware, power units, cooling and software), and holistically work to boost data center energy efficiency and performance. In particular, this paper proposes (a) architectural principles for energy-efficient management of Clouds; (b) energy-efficient resource allocation policies and scheduling algorithms considering quality-of-service expectations, and devices power usage characteristics; and (c) a novel software technology for energy-efficient management of Clouds. We have validated our approach by conducting a set of rigorous performance evaluation study using the CloudSim toolkit. The results demonstrate that Cloud computing model has immense potential as it offers significant performance gains as regards to response time and cost saving under dynamic workload scenarios.

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.

Fitting soft center-near design multifocal lenses

The recent launch of the Air Optix Aqua Multifocal lens (Ciba Vision) means that there are three silicone hydrogel (SiHy) multifocal lenses available. The benefits of SiHy materials have been well documented (Dumbleton, 2006), but until recently they weren't available in multifocal designs. With an aging population, it's likely that a large number of contact lens wearers are approaching presbyopia, which will result in a dramatic increase in demand for multifocal lenses.