Multilinear function factorisation for time series feature extraction

This work applies a variety of multilinear function factorisation techniques to extract appropriate features or attributes from high dimensional multivariate time series for classification. Recently, a great deal of work has centred around designing time series classifiers using more and more complex feature extraction and machine learning schemes. This paper argues that complex learners and domain specific feature extraction schemes of this type are not necessarily needed for time series classification, as excellent classification results can be obtained by simply applying a number of existing matrix factorisation or linear projection techniques, which are simple and computationally inexpensive. We highlight this using a geometric separability measure and classification accuracies obtained though experiments on four different high dimensional multivariate time series datasets. © 2013 IEEE.

Electrical/optical dual-function redox potential transistor

We demonstrate a new type of transistors, the electrical/optical "dual-function redox-potential transistors", which is solution processable and environmentally stable. This device consists of vertically staked electrodes that act as gate, emitter and collector. It can perform as a normal transistor, whilst one electrode which is sensitised by dye enables to generate photocurrent when illuminated. Solution processable oxide-nanoparticles were used to form various functional layers, which allow an electrolyte to penetrate through and, consequently, the current between emitter and collector can be controlled by the gate potential modulated distribution of ions. The result here shows that the device performs with high ON-current under low driving voltage (<1â€...V), while the transistor performance can readily be controlled by photo-illumination. Such device with combined optical and electrical functionalities allows single device to perform the tasks that are usually done by a circuit/system with multiple optical and electrical components, and it is promising for various applications.

SLP: A zero-contact non-invasive method for pulmonary function testing

Structured Light Plethysmography (SLP) is a novel non-invasive method that uses structured light to perform pulmonary function testing that does not require physical contact with a patient. The technique produces an estimate of chest wall volume changes over time. A patient is observed continuously by two cameras and a known pattern of light (i.e. structured light) is projected onto the chest using an off-the-shelf projector. Corner features from the projected light pattern are extracted, tracked and brought into correspondence for both camera views over successive frames. A novel self calibration algorithm recovers the intrinsic and extrinsic camera parameters from these point correspondences. This information is used to reconstruct a surface approximation of the chest wall and several novel ideas for 'cleaning up' the reconstruction are used. The resulting volume and derived statistics (e.g. FVC, FEV) agree very well with data taken with a spirometer. © 2010. The copyright of this document resides with its authors.