An environment for studying the impact of spatialising sonified graphs on data comprehension

We describe AudioCave, an environment for exploring the impact of spatialising sonified graphs on a set of numerical data comprehension tasks. Its design builds on findings regarding the effectiveness of sonified graphs for numerical data overview and discovery by visually impaired and blind students. We demonstrate its use as a test bed for comparing the approach of accessing a single sonified numerical datum at a time to one where multiple sonified numerical data can be accessed concurrently. Results from this experiment show that concurrent access facilitates the tackling of our set multivariate data comprehension tasks. AudioCave also demonstrates how the spatialisation of the sonified graphs provides opportunities for sharing the representation. We present two experiments investigating users solving set data comprehension tasks collaboratively by sharing the data representation

A Survey of Brain Inspired Technologies for Engineering

Cognitive engineering is a multi-disciplinary field and hence it is difficult to find a review article consolidating the leading developments in the field. The in-credible pace at which technology is advancing pushes the boundaries of what is achievable in cognitive engineering. There are also differing approaches to cognitive engineering brought about from the multi-disciplinary nature of the field and the vastness of possible applications. Thus research communities require more frequent reviews to keep up to date with the latest trends. In this paper we shall dis-cuss some of the approaches to cognitive engineering holistically to clarify the reasoning behind the different approaches and to highlight their strengths and weaknesses. We shall then show how developments from seemingly disjointed views could be integrated to achieve the same goal of creating cognitive machines. By reviewing the major contributions in the different fields and showing the potential for a combined approach, this work intends to assist the research community in devising more unified methods and techniques for developing cognitive machines

Photoelastic stress analysis under unconventional loading

This paper presents use of conventional photoelastic techniques under unconventional loading situations to evaluate their efficacy in sensing applications. The loading is unconventional in the sense that low modulus photoelastic material is deformed under vertical load in the direction of light travel to induce the photoelastic effect. This is atypical of conventional methods where loading is across the light travel. Both RGB calibration and phase shining techniques have been used to study the characteristics of fringe patterns obtained under vertical and shear loads. The results obtained under these conditions are discussed with their limitations specially when this is applied for sensing applications. Finally a case study has been conducted to analyze the foot image and conclusions drawn from this have been presented. Copyright © 2007 by ASME

Optimal analog wavelet bases construction using hybrid optimization algorithm

An approach for the construction of optimal analog wavelet bases is presented. First, the definition of an analog wavelet is given. Based on the definition and the least-squares error criterion, a general framework for designing optimal analog wavelet bases is established, which is one of difficult nonlinear constrained optimization problems. Then, to solve this problem, a hybrid algorithm by combining chaotic map particle swarm optimization (CPSO) with local sequential quadratic programming (SQP) is proposed. CPSO is an improved PSO in which the saw tooth chaotic map is used to raise its global search ability. CPSO is a global optimizer to search the estimates of the global solution, while the SQP is employed for the local search and refining the estimates. Benefiting from good global search ability of CPSO and powerful local search ability of SQP, a high-precision global optimum in this problem can be gained. Finally, a series of optimal analog wavelet bases are constructed using the hybrid algorithm. The proposed method is tested for various wavelet bases and the improved performance is compared with previous works.Peer reviewedFinal Published versio