Bayesian Online Changepoint Detection

Changepoints are abrupt variations in the generative parameters of a data sequence. Online detection of changepoints is useful in modelling and prediction of time series in application areas such as finance, biometrics, and robotics. While frequentist methods have yielded online filtering and prediction techniques, most Bayesian papers have focused on the retrospective segmentation problem. Here we examine the case where the model parameters before and after the changepoint are independent and we derive an online algorithm for exact inference of the most recent changepoint. We compute the probability distribution of the length of the current ``run,'' or time since the last changepoint, using a simple message-passing algorithm. Our implementation is highly modular so that the algorithm may be applied to a variety of types of data. We illustrate this modularity by demonstrating the algorithm on three different real-world data sets.

Stability enhancement by casing grooves: The importance of stall inception mechanism and solidity

This paper concerns the optimisation of casing grooves and the important influence of stall inception mechanism on groove performance. Installing casing grooves is a well known technique for improving the stable operating range of a compressor, but the wide-spread use of grooves is restricted by the loss of efficiency and flow capacity. In this paper, laboratory tests are used to examine the conditions under which casing treatment can be used to greatest effect. The use of a single casing groove was investigated in a recently published companion paper. The current work extends this to multiple-groove treatments and considers their performance in relation to stall inception mechanisms. Here it is shown that the stall margin gain from multiple grooves is less than the sum of the gains if the grooves were used individually. By contrast, the loss of efficiency is additive as the number of grooves increases. It is then shown that casing grooves give the greatest stall margin improvement when used in a compressor which exhibits spike-type stall inception, while modal activity before stall can dramatically reduce the effectiveness of the grooves. This finding highlights the importance of being able to predict the stall inception mechanism which might occur in a given compressor before and after grooves are added. Some published prediction techniques are therefore examined, but found wanting. Lastly, it is shown that casing grooves can, in some cases, be used to remove rotor blades and produce a more efficient, stable and light-weight rotor. © 2010 by ASME.

Predictive techniques for turbulent oscillatory flows

The prediction of turbulent oscillatory flow at around transitional Reynolds numbers is considered for an idealized electronics system. To assess the accuracy of turbulence models, comparison is made with measurements. A stochastic procedure is used to recover instantaneous velocity time traces from predictions. This procedure enables more direct comparison with turbulence intensity measurements which have not been filtered to remove the oscillatory flow component. Normal wall distances, required in some turbulence models, are evaluated using a modified Poisson equation based technique. A range of zero, one and two equation turbulence models are tested, including zonal and a non-linear eddy viscosity models. The non-linear and zonal models showed potential for accuracy improvements.

An example of the use of neural computing techniques in materials science - The modelling of fatigue thresholds in Ni-base superalloys

Two adaptive numerical modelling techniques have been applied to prediction of fatigue thresholds in Ni-base superalloys. A Bayesian neural network and a neurofuzzy network have been compared, both of which have the ability to automatically adjust the network's complexity to the current dataset. In both cases, despite inevitable data restrictions, threshold values have been modelled with some degree of success. However, it is argued in this paper that the neurofuzzy modelling approach offers real benefits over the use of a classical neural network as the mathematical complexity of the relationships can be restricted to allow for the paucity of data, and the linguistic fuzzy rules produced allow assessment of the model without extensive interrogation and examination using a hypothetical dataset. The additive neurofuzzy network structure means that redundant inputs can be excluded from the model and simple sub-networks produced which represent global output trends. Both of these aspects are important for final verification and validation of the information extracted from the numerical data. In some situations neurofuzzy networks may require less data to produce a stable solution, and may be easier to verify in the light of existing physical understanding because of the production of transparent linguistic rules. © 1999 Elsevier Science S.A.

Evaluation of manufacturing techniques for a minifluidics demonstrator system

A multi-disciplinary team based at Heriot-Watt University and other Universities has been set up to tackle the design and manufacturing of lab-on-a-chip for industries as one of the demonstrators of the EPSRC Grand Challenge project "3D-Mintegration". The team focuses on the analysis of foetal genetic material extracted from maternal blood as a smart alternative to invasive prenatal testing such as amniocentesis. The first module of the microsystem envisaged achieves a separation of blood cells from plasma. This system permits the testing of different manufacturing techniques.

Evaluation of termination techniques for 4H-SiC PiN diodes and trench JFETs

An investigation concerning suitable termination techniques for 4H-SiC trench JFETs is presented. Field plates, p+ floating rings and junction termination extension techniques are used to terminate 1.2kV class PiN diodes. The fabricated PiN diodes evaluated here have a similar design to trench JFETs. Therefore, the conclusions for PiN diodes can be applied to JFET structures as well. Numerical simulations are also used to illustrate the effect of the terminations on the diodes' blocking mode behaviour.