Super Blooper? Time to halt the superannuation juggernaut?

The superannuation industry has increased almost exponentially in Australia over the past decade. The main reason for this is because government  regulation compels employers to pay a fixed portion of employees’ salary  towards superannuation. In this article we suggest that the unremitting  government policy of coercing money towards superannuation is flawed. Superannuation is wrong at two levels. First, on an economic analysis, the evidence does not suggest that (i) individuals who invest in superannuation are necessarily better off than those who apply their income elsewhere; and (ii) there is no evidence that absent a coercive superannuation scheme the government will be unable to sustain people into their old age. Second, at the human and societal level, studies of human well-being show that coercing people to make spending decisions is inimical to human happiness. People flourish best when they are in control of their activities, including their finances. Left to their own devices, many people will not save for a rainy day; however, on balance it is probably better off to be a bit poorer in retirement than to have been deprived of the opportunity to spend 9% of one’s income over the period of one’s working life – when one’s needs are the greatest. Compulsory superannuation should be abolished. Money currently paid as a compulsory superannuation contribution should instead be paid to the employee as a salary.

Multi-wavelets from B-spline super-functions with approximation order

Approximation order is an important feature of all wavelets. It implies that polynomials up to degree p−1 are in the space spanned by the scaling function(s). In the scalar case, the scalar sum rules determine the approximation order or the left eigenvectors of the infinite down-sampled convolution matrix H determine the combinations of scaling functions required to produce the desired polynomial. For multi-wavelets the condition for approximation order is similar to the conditions in the scalar case. Generalized left eigenvectors of the matrix H_f; a finite portion of H determines the combinations of scaling functions that produce the desired superfunction from which polynomials of desired degree can be reproduced. The superfunctions in this work are taken to be B-splines. However, any refinable function can serve as the superfunction. The condition of approximation order is derived and new, symmetric, compactly supported and orthogonal multi-wavelets with approximation orders one, two, three and four are constructed.

Super water repellent fabrics produced by silica nanoparticle-containing coating

In this paper, we report on superhydrophobic fabrics (polyester, wool and cotton) produced by a wet-chemical coating technique. The coating solutions were synthesized by the co-hydrolysis of two silane precursors, tetraethyl orthosilicate (TEOS) and an alkylsilane, in an alkaline condition. Without any purification, the as-hydrolyzed solutions were directly used to treat fabrics, and the treated fabrics had water contact angles (CA) as high as 170º and sliding angles (SA) as low as 5º. Three alkylsilanes have been used for the synthesis of the coating solutions, and all contain three hydrolysable alkoxyl groups and one non-hydrolysable alkyl, but with different chain lengths (C1, C8 and C16). It was found that the CA value increased with an increase in the alkyl chain length, while the SA showed a reverse trend. When the functional group had a C16 alkyl, the treated fabric surfaces were highly superhydrophobic, with the CA not being affected much by the fabric type, while the SA values were slightly affected by the original wettability of the fabric substrates. The superhydrophobic feature was attributed to a highly rough surface formed by the particulate coating. Aside from the superhydrophobicity, the influence of the coating on the fabric softness was also examined.

Making difference SUPER : a critical approach to the politics of celebrity-authored children's books

Recent years have seen a flood of celebrity-authored children’s books enter the children’s literature marketplace. This paper tracks the evolution of this phenomenon as it pertains to contemporary celebrity culture, and responds to the question: what are the embedded messages about identity at play in such texts? The key contention here is that these works endorse celebrity as the most desirable identity category for the children of the new millennium, going so far as to position difference as a commodity to be traded in the quest for fame. Using critical theory around celebrity culture, and through a close reading of a short celebrity-authored picture book, this paper demonstrates that far from being innocuous pieces of popular culture, such books beckon children into a world that increasingly values visibility and stardom above all else.

Super-realistic rendering using real-time tweening

The realism of contemporary computer graphics (and especially Virtual Reality {VR}) is limited by the great computational cost of rendering objects of appropriate complexity with convincing lighting and surface effects. We introduce a framework that allows rendering of objects in true photographic quality using tweening. The simple but effective design of our system allows us not only to perform the necessary operations in real-time on standard hardware, but also achieve other effects like morphing. Furthermore, it is shown how our system can be gainfully employed in non-VR contexts like extreme low-bandwidth video-conferencing and others.

Learning to think, learning to learn : super teaching for super success

The early childhood years are a busy, exciting time. New discoveries, skills and competencies are a regular part of life for a young child. Early childhood teachers have the opportunity to optimise these amazing and important years. In this paper, I will discuss teaching strategies that can turn children’s possibilities into realities. The practices that will be discussed involve expanding thinking, problem-solving and developing hypotheses. These teaching strategies can build on children’s learning dispositions and their strengths and interests to put the ‘wow factor’ into learning.

Super-resolution of a 3-dimensional scene from novel viewpoints

Super-resolution is a method of post-processing image enhancement that increases the spatial resolution of video or images. Existing super-resolution techniques apply only to images captured of a planar scene. This paper aims to extend super-resolution concepts from the 2D domain to the 3D domain, drawing on ideas from both superresolution and multi-view geometry, two fields of research that until now have predominantly been studied in isolation. 2D super-resolution methods are not without their complexities and limitations. However, once multiple views of a scene are considered within a super-resolution framework, a new range of issues arise that must also be resolved. For example, when input images of a scene with variation in depth are considered, it is no longer clear how and where the images should be registered. This paper describes the use of sparse 3D reconstruction in order to ‘register’ the input images, which are then transferred to a novel image plane and combined to increase the perceived detail in the scene. Experimental results using real images captured from generally positioned input cameras are presented.

Performance evaluation of multi-frame super-resolution algorithms

Multi-frame super-resolution algorithms aim to increase spatial resolution by fusing information from several low-resolution perspectives of a scene. While a wide array of super-resolution algorithms now exist, the comparative capability of these techniques in practical scenarios has not been adequately explored. In addition, a standard quantitative method for assessing the relative merit of super-resolution algorithms is required. This paper presents a comprehensive practical comparison of existing super-resolution techniques using a shared platform and 4 common greyscale reference images. In total, 13 different super-resolution algorithms are evaluated, and as accurate alignment is critical to the super-resolution process, 6 registration algorithms are also included in the analysis. Pixel-based visual information fidelity (VIFP) is selected from the 12 image quality metrics reviewed as the measure most suited to the appraisal of super-resolved images. Experimental results show that Bayesian super-resolution methods utilizing the simultaneous autoregressive (SAR) prior produce the highest quality images when combined with generalized stochastic Lucas-Kanade optical flow registration.