Application of neural networks to the ranking of perinatal variables influencing birthweight.

In this paper we compare Multi-Layer Perceptrons (a neural network type) with Multivariate Linear Regression in predicting birthweight from nine perinatal variables which are thought to be related. Results show, that seven of the nine variables, i.e., gestational age, mother's body-mass index (BMI), sex of the baby, mother's height, smoking, parity and gravidity, are related to birthweight. We found no significant relationship between birthweight and each of the two variables, i.e., maternal age and social class.

Automated meshing for aero-thermal analysis of complex automotive geometries

Successful product development, especially in motorsport, increasingly depends not just on the ability to simulate aero-thermal behavior of complex geometrical configurations, but also the ability to automate these simulations within a workflow and perform as many simulations as possible within constrained time frames. The core of these aero-thermal simulations - and usually the main bottleneck - is generating the computational mesh. This paper describes recent work aimed at developing a mesh generator which can reliably produce meshes for geometries of essentially arbitrary complexity in an automated manner and fast enough to keep up with the pace of an engineering development program. Our goal is to be able to script the mesh generation within an automated workflow - and forget it. © 2011 SAE International.

Hybrid LES - RANS of complex geometry jets

Large eddy simulation (LES) type studies are made of a realistic geometry coaxial nozzle with a pylon. For the LES, since the solver being used tends towards having dissipative qualities, the subgrid scale (SGS) model is omitted, giving Numerical LES (NLES). To overcome near wall streak resolution problems a near wall RANS (Reynolds averaged Navier Stokes) model is used giving a hybrid NLES-RANS approach.The pylon is shown to influence the flow development, having a significant impact on peak turbulence levels and spreading rates. The results show that real geometry effects are influential and should be taken into account when moving towards real engine simulations. If their effects are ignored then, based on the studies here, key turbulence parameters will have significant error.

Coarse-level object recognition using interlevel products of complex wavelets

This paper introduces the Interlevel Product (ILP) which is a transform based upon the Dual-Tree Complex Wavelet. Coefficients of the ILP have complex values whose magnitudes indicate the amplitude of multilevel features, and whose phases indicate the nature of these features (e.g. ridges vs. edges). In particular, the phases of ILP coefficients are approximately invariant to small shifts in the original images. We accordingly introduce this transform as a solution to coarse scale template matching, where alignment concerns between decimation of a target and decimation of a larger search image can be mitigated, and computational efficiency can be maintained. Furthermore, template matching with ILP coefficients can provide several intuitive "near-matches" that may be of interest in image retrieval applications. © 2005 IEEE.

Statistical image modelling using interscale phase relationships of complex wavelet coefficients

A novel method for modelling the statistics of 2D photographic images useful in image restoration is defined. The new method is based on the Dual Tree Complex Wavelet Transform (DT-CWT) but a phase rotation is applied to the coefficients to create complex coefficients whose phase is shift-invariant at multiscale edge and ridge features. This is in addition to the magnitude shift invariance achieved by the DT-CWT. The increased correlation between coefficients adjacent in space and scale provides an improved mechanism for signal estimation. © 2006 IEEE.

On the functions of products

Understanding the performance and manner of functioning of existing products is at the base of new product development activities. In engineering design the term function is generally used to refer to the technical actions performed by a product. However, products accomplish a wider range of goals. This research explores the opportunity to describe and model, through the concept of function, product actions across four dimensions including technical, aesthetic, social and economic. The research demonstrates that non-technical functions can be represented through active verbs and nouns and modelled using a method known as the Function Analysis Diagram (FAD). The research argues that when technical, aesthetic, social and economic perspectives on product development are considered as different types of function, stakeholders have a common language to communicate which can benefit design collaboration.