Evidence for on-line visual guidance during saccadic gaze shifts.

Rapid orientating movements of the eyes are believed to be controlled ballistically. The mechanism underlying this control is thought to involve a comparison between the desired displacement of the eye and an estimate of its actual position (obtained from the integration of the eye velocity signal). This study shows, however, that under certain circumstances fast gaze movements may be controlled quite differently and may involve mechanisms which use visual information to guide movements prospectively. Subjects were required to make large gaze shifts in yaw towards a target whose location and motion were unknown prior to movement onset. Six of those tested demonstrated remarkable accuracy when making gaze shifts towards a target that appeared during their ongoing movement. In fact their level of accuracy was not significantly different from that shown when they performed a 'remembered' gaze shift to a known stationary target (F-3,F-15 = 0.15, p > 0.05). The lack of a stereotypical relationship between the skew of the gaze velocity profile and movement duration indicates that on-line modifications were being made. It is suggested that a fast route from the retina to the superior colliculus could account for this behaviour and that models of oculomotor control need to be updated.

On-line Emotion Recognition in a 3-D Activation-Valence-Time Continuum using Acoustic and Linguistic Cues

For many applications of emotion recognition, such as virtual agents, the system must select responses while the user is speaking. This requires reliable on-line recognition of the user’s affect. However most emotion recognition systems are based on turnwise processing. We present a novel approach to on-line emotion recognition from speech using Long Short-Term Memory Recurrent Neural Networks. Emotion is recognised frame-wise in a two-dimensional valence-activation continuum. In contrast to current state-of-the-art approaches, recognition is performed on low-level signal frames, similar to those used for speech recognition. No statistical functionals are applied to low-level feature contours. Framing at a higher level is therefore unnecessary and regression outputs can be produced in real-time for every low-level input frame. We also investigate the benefits of including linguistic features on the signal frame level obtained by a keyword spotter.

Enabling Free On-line Access to UK Law Reports: The Copyright Problem

The history of publishing legal decisions (law reporting) in the UK has been that of a privatised system since its inception, and that history has encompassed several hundred years. The privatised nature of this has meant that the product (the law report) has been, except in limited cases, viewed as the property of the publisher, rather than the property of the court or public. BAILII is an open access legal database that came about in part because of the copyrighted, privatised nature of this legal information. In this paper, we will outline the problem of access to pre-2000 judgments in the UK and consider whether there are legal or other remedies which might enable BAILII to both develop a richer historic database and also to work in harmony, rather than in competition, with legal publishers. We argue that public access to case law is an essential requirement in a democratic common law system, and that BAILII should be seen as a potential step towards a National Law Library.

Fast automatic two-stage nonlinear model identification based on the extreme learning machine

It is convenient and effective to solve nonlinear problems with a model that has a linear-in-the-parameters (LITP) structure. However, the nonlinear parameters (e.g. the width of Gaussian function) of each model term needs to be pre-determined either from expert experience or through exhaustive search. An alternative approach is to optimize them by a gradient-based technique (e.g. Newton’s method). Unfortunately, all of these methods still need a lot of computations. Recently, the extreme learning machine (ELM) has shown its advantages in terms of fast learning from data, but the sparsity of the constructed model cannot be guaranteed. This paper proposes a novel algorithm for automatic construction of a nonlinear system model based on the extreme learning machine. This is achieved by effectively integrating the ELM and leave-one-out (LOO) cross validation with our two-stage stepwise construction procedure [1]. The main objective is to improve the compactness and generalization capability of the model constructed by the ELM method. Numerical analysis shows that the proposed algorithm only involves about half of the computation of orthogonal least squares (OLS) based method. Simulation examples are included to confirm the efficacy and superiority of the proposed technique.

Constant scale factor, on-line CORDIC algorithm in the circular coordinate system

Real time digital signal processing requires the development of high performance arithmetic algorithms suitable for VLSI design. In this paper, a new online, circular coordinate system CORDIC algorithm is described, which has a constant scale factor. This algorithm was developed using a new Angular Representation (AR) model A radix 2 version of the CORDIC algorithm is presented, along with an architecture suitable for VLSI implementation.

Effect of environmental multipath on line of sight body to body communication at 2.45 GHz

Body to body links are the most scenario dependent form of body centric communications with performance highly dependent on the users' movements, relative positioning and the local operating environment. This paper focuses on line of sight cases which although they should be the most dependent, still have considerable variability depending on local propagation conditions. The results presented in the paper also raise important questions about the statistical characterisation of such links and the effect of different approaches to local mean averaging on fading characteristics. © 2012 IEEE.

On-line FTIR spectroscopic investigations of methanol oxidation in a direct methanol fuel cell

A real-time Fourier transform infrared spectroscopy (FTIRS) analysis of the products of methanol oxidation in a prototype direct-methanol fuel cell operating at high temperatures (150 to 185°C) is reported here. The methanol oxidation products on platinum black and platinum-ruthenium catalyst surfaces were determined as a function of the fuel cell operating temperature, current density, and methanol/water mole ratio. Neither formaldehyde nor formic acid was detected in anode exhaust gas at all cell operating conditions. The product distributions of methanol oxidation obtained by on-line FTIRS are consistent with our previous results obtained by on-line mass spectroscopy under similar conditions. With pure methanol in anode feed, methanaldimethylacetal was found to be the main product, methyl formate and CO were also found. However, when water was present in the anode feed, the main product was CO , and the formation of methanaldimethylacetal and methyl formate decreased significantly with increase of the water/methanol mole ratio. Increase of cell operating temperature enhanced the formation of CO and decreased the formation of methanaldimethylacetal and methyl formate. Pt/Ru catalyst is more active for methanol oxidation and has a higher selectivity toward CO formation than Pt-black. Nearly complete methanol oxidation, i.e., the product was almost exclusively CO , was achieved using a Pt/Ru catalyst and a water/methanol mole ratio of 2 or higher in the anode feed at a temperature of 185°C or above.