On the efficacy of techniques for evaluating multivariate volatility forecasts

The performance of techniques for evaluating multivariate volatility forecasts are not yet as well understood as their univariate counterparts. This paper aims to evaluate the efficacy of a range of traditional statistical-based methods for multivariate forecast evaluation together with methods based on underlying considerations of economic theory. It is found that a statistical-based method based on likelihood theory and an economic loss function based on portfolio variance are the most effective means of identifying optimal forecasts of conditional covariance matrices.

Towards an integration of the theory of planned behaviour and cognitive behavioural strategies : an example from a school-based injury prevention programme

Adolescent risk-taking behavior has potentially serious injury consequences and school-based behavior change programs provide potential for reducing such harm. A well-designed program is likely to be theory-based and ecologically valid however it is rare that the operationalisation process of theories is described. The aim of this paper is to outline how the Theory of Planned Behavior and Cognitive Behavioral Therapy informed intervention design in a school setting. Teacher interviews provided insights into strategies that might be implemented within the curriculum and provided detail used to operationalise theory constructs. Benefits and challenges in applying both theories are described with examples from an injury prevention program, Skills for Preventing Injury in Youth.

Determining the detection capabilities of existing real time measurement techniques for different engineered nanoparticles

The application of nanotechnology products has increased significantly in recent years. With their broad range of applications, including electronics, food and agriculture, power and energy, scientific instruments, clothing, cosmetics, buildings, biomedical and health, etc (Catanzariti, 2008), nanomaterials are an indispensible part of human life.

A model for curricula integration using the Australian curriculum

Targeting students’ learning is at the centre of education. In addition, education is promoted as a solution on various issues; consequently educators seek ways for teachers to address societal needs, students’ learning needs, and the overcrowded curriculum. There are definition debates and issues around integrating curricula. However, the rationale for primary students undertaking curricula integrated learning can provide motivation for primary teachers to devise and implement curricula integrated lessons in the classroom. More exploration is required to present models for the practical implementation of curricula integration. This paper provides practical ideas for curricula integration that focus on combining achievement standards from the Australian Curriculum: Science and other key learning areas.

Visualisation of complex flows using texture-based techniques

Complex flow datasets are often difficult to represent in detail using traditional vector visualisation techniques such as arrow plots and streamlines. This is particularly true when the flow regime changes in time. Texture-based techniques, which are based on the advection of dense textures, are novel techniques for visualising such flows (i.e., complex dynamics and time-dependent). In this paper, we review two popular texture-based techniques and their application to flow datasets sourced from real research projects. The texture-based techniques investigated were Line Integral Convolution (LIC), and Image-Based Flow Visualisation (IBFV). We evaluated these techniques and in this paper report on their visualisation effectiveness (when compared with traditional techniques), their ease of implementation, and their computational overhead.

From the editor

In order to read this Project Management Journal issue, I suggest embracing a modeling perspective. Talking about modeling should lead me to define what is meant by “model” and to develop some kind of categorization, classification, or taxonomy of models. One can consider basic categories like quantitative vs. qualitative, explanatory vs. predictive, stochastic, nonstochastic mathematical, or qualitative models, linear vs. nonlinear and their underlying assumptions, degree of simplification, systemic effects integration, and so on...

Performance assessment of exponential Rosenbrock method for large systems of ODE

This paper studies time integration methods for large stiff systems of ordinary differential equations (ODEs) of the form u'(t) = g(u(t)). For such problems, implicit methods generally outperform explicit methods, since the time step is usually less restricted by stability constraints. Recently, however, explicit so-called exponential integrators have become popular for stiff problems due to their favourable stability properties. These methods use matrix-vector products involving exponential-like functions of the Jacobian matrix, which can be approximated using Krylov subspace methods that require only matrix-vector products with the Jacobian. In this paper, we implement exponential integrators of second, third and fourth order and demonstrate that they are competitive with well-established approaches based on the backward differentiation formulas and a preconditioned Newton-Krylov solution strategy.

Prostate cancer biomarkers and the emerging proteomic techniques used in biomarker research

Prostate cancer (CaP) is the second leading cause of cancer-related deaths in North American males and the most common newly diagnosed cancer in men world wide. Biomarkers are widely used for both early detection and prognostic tests for cancer. The current, commonly used biomarker for CaP is serum prostate specific antigen (PSA). However, the specificity of this biomarker is low as its serum level is not only increased in CaP but also in various other diseases, with age and even body mass index. Human body fluids provide an excellent resource for the discovery of biomarkers, with the advantage over tissue/biopsy samples of their ease of access, due to the less invasive nature of collection. However, their analysis presents challenges in terms of variability and validation. Blood and urine are two human body fluids commonly used for CaP research, but their proteomic analyses are limited both by the large dynamic range of protein abundance making detection of low abundance proteins difficult and in the case of urine, by the high salt concentration. To overcome these challenges, different techniques for removal of high abundance proteins and enrichment of low abundance proteins are used. Their applications and limitations are discussed in this review. A number of innovative proteomic techniques have improved detection of biomarkers. They include two dimensional differential gel electrophoresis (2D-DIGE), quantitative mass spectrometry (MS) and functional proteomic studies, i.e., investigating the association of post translational modifications (PTMs) such as phosphorylation, glycosylation and protein degradation. The recent development of quantitative MS techniques such as stable isotope labeling with amino acids in cell culture (SILAC), isobaric tags for relative and absolute quantitation (iTRAQ) and multiple reaction monitoring (MRM) have allowed proteomic researchers to quantitatively compare data from different samples. 2D-DIGE has greatly improved the statistical power of classical 2D gel analysis by introducing an internal control. This chapter aims to review novel CaP biomarkers as well as to discuss current trends in biomarker research from two angles: the source of biomarkers (particularly human body fluids such as blood and urine), and emerging proteomic approaches for biomarker research.

TiltZoom : tilt-based zooming control for easy one-handed mobile interactions

In this paper, we present TiltZoom, a collection of tilt-based interaction techniques designed for easy one-handed zooming on mobile devices. TiltZoom represents novel gestural interaction techniques, implemented using rate-of-rotation readings from a gyroscope, a sensor commonly embedded on current generation smart phones. We designed and experimented three variants of TiltZoom - Tilt Level, Tilt and Hold and Flip Gesture. The design decisions for all three variants are discussed in this paper and their performance, as well as subjective user experience are evaluated and compared against conventional touch-based zooming techniques. TiltZoom appears to be a worthy addition to current established collection of gesture-based mobile interaction techniques for zooming controls, especially when user has only one hand available when moving about.

Design Integration Workshops 2012

Businesses will learn how design integration can increase growth and productivity, and gain a sustainable competitive advantage. This hands on two-day workshop will demystify design thinking and introduce you to both theory and practice for the latest, world-class design integration methods. Design integration will transform your business and boost resilience in the face of current global, social and economic challenges.

First year design "Visualisation II": The hybridisation of analogue and digital tools

This paper discusses first year students’ responses and outcomes to the integration of digital technologies in their second semester foundational visualisation class; ‘Visualisation II’. As the second class in the Visualisation series, previous analogue knowledge taught in ‘Visualisation I’ is compounded with new digital technologies establishing the introduction to a myriad of hybrid visualisation tools and techniques for design exploration and design artefact. This research examines the differentiation between analogue and digital design, common precedents of the two, and reflects upon the environment and class structure with the learning experiences and confidence of surveyed participants.

Non-parametric techniques for fast and robust stereo matching

The mining environment presents a challenging prospect for stereo vision. Our objective is to produce a stereo vision sensor suited to close-range scenes consisting mostly of rocks. This sensor should produce a dense depth map within real-time constraints. Speed and robustness are of foremost importance for this application. This paper compares a number of stereo matching algorithms in terms of robustness and suitability to fast implementation. These include traditional area-based algorithms, and algorithms based on non-parametric transforms, notably the rank and census transforms. Our experimental results show that the rank and census transforms are robust with respect to radiometric distortion and introduce less computational complexity than conventional area-based matching techniques.

An ingenuous Decision Support System (iDSS) approach for remote area pregnant women

This paper addresses development of an ingenious decision support system (iDSS) based on the methodology of survey instruments and identification of significant variables to be used in iDSS using statistical analysis. A survey was undertaken with pregnant women and factorial experimental design was chosen to acquire sample size. Variables with good reliability in any one of the statistical techniques such as Chi-square, Cronbach’s α and Classification Tree were incorporated in the iDSS. The ingenious decision support system was implemented with Visual Basic as front end and Microsoft SQL server management as backend. Outcome of the ingenious decision support system include advice on Symptoms, Diet and Exercise to pregnant women.