Effects of syllabic complexity in predicting accuracy of repetition and direction of errors in patients with articulatory and phonological difficulties

The purpose of this paper is to demonstrate the existence of a strong and significant effect of complexity in aphasia independent from other variables including length. Complexity was found to be a strong and significant predictor of accurate repetition in a group of 13 Italian aphasic patients when it was entered in a regression equation either simultaneously or after a large number of other variables. Significant effects were found both when complexity was measured in terms of number of complex onsets (as in a recent paper by Nickels & Howard, 2004) and when it was measured in a more comprehensive way. Significant complexity effects were also found with matched lists contrasting simple and complex words and in analyses of errors. Effects of complexity, however, were restricted to patients with articulatory difficulties. Reasons for this association and for the lack of significant results in Nickels and Howard (2004) are discussed. © 2005 Psychology Press Ltd.

The effect of spectral filters on reading speed and accuracy following stroke

Purpose - The aim of the study was to determine the effect of optimal spectral filters on reading performance following stroke. Methods - Seventeen stroke subjects, aged 43-85, were considered with an age-matched Control Group (n = 17). Subjects undertook the Wilkins Rate of Reading Test on three occasions: (i) using an optimally selected spectral filter; (ii) subjects were randomly assigned to two groups: Group 1 used an optimal filter, whereas Group 2 used a grey filter, for two-weeks. The grey filter had similar photopic reflectance to the optimal filters, intended as a surrogate for a placebo; (iii) the groups were crossed over with Group 1 using a grey filter and Group 2 given an optimal filter, for two weeks, before undertaking the task once more. An increase in reading speed of >5% was considered clinically relevant. Results - Initial use of a spectral filter in the stroke cohort, increased reading speed by ~8%, almost halving error scores, findings not replicated in controls. Prolonged use of an optimal spectral filter increased reading speed by >9% for stroke subjects; errors more than halved. When the same subjects switched to using a grey filter, reading speed reduced by ~4%. A second group of stroke subjects used a grey filter first; reading speed decreased by ~3% but increased by ~4% with an optimal filter, with error scores almost halving. Conclusions - The present study has shown that spectral filters can immediately improve reading speed and accuracy following stroke, whereas prolonged use does not increase these benefits significantly. © 2013 Spanish General Council of Optometry.

Reduced attentional capacity, but normal processing speed and shifting of attention in developmental dyslexia: evidence from a serial task

We report the performance of a group of adult dyslexics and matched controls in an array-matching task where two strings of either consonants or symbols are presented side by side and have to be judged to be the same or different. The arrays may differ either in the order or identity of two adjacent characters. This task does not require naming – which has been argued to be the cause of dyslexics’ difficulty in processing visual arrays – but, instead, has a strong serial component as demonstrated by the fact that, in both groups, Reaction times (RTs) increase monotonically with position of a mismatch. The dyslexics are clearly impaired in all conditions and performance in the identity conditions predicts performance across orthographic tasks even after age, performance IQ and phonology are partialled out. Moreover, the shapes of serial position curves are revealing of the underlying impairment. In the dyslexics, RTs increase with position at the same rate as in the controls (lines are parallel) ruling out reduced processing speed or difficulties in shifting attention. Instead, error rates show a catastrophic increase for positions which are either searched later or more subject to interference. These results are consistent with a reduction in the attentional capacity needed in a serial task to bind together identity and positional information. This capacity is best seen as a reduction in the number of spotlights into which attention can be split to process information at different locations rather than as a more generic reduction of resources which would also affect processing the details of single objects.

Detection and direction-discrimination of diotic and dichotic ramp modulations in amplitude and phase

When the source of a tone moves with respect to a listener's ears, dichotic (or interaural) phase and amplitude modulations (PM and AM) are produced. Two experiments investigated the psychophysical characteristics of dichotic linear ramp modulations in phase and amplitude, and compared them with the psychophysics of diotic PM and AM. In experiment 1, subjects were substantially more sensitive to dichotic PM than diotic PM, but AM sensitivity was equivalent in the dichotic and diotic conditions. Thresholds for discriminating modulation direction were smaller than detection thresholds for dichotic AM, and both diotic AM and PM. Dichotic PM discrimination thresholds were similar to detection thresholds. In experiment 2, the effects of ramp duration were examined. Sensitivity to dichotic AM and PM, and diotic AM increased as duration was increased from 20 ms to 200 ms. The functions relating sensitivity to ramp duration differed across the stimuli; sensitivity to dichotic PM increased more rapidly than sensitivity to dichotic or diotic AM. This was also reflected in shorter time-constants and minimum integration times for dichotic PM detection. These findings support the hypothesis that the analysis of dichotic PM and AM rely on separate mechanisms. © 2003 Acoustical Society of America.

High speed and high resolution demodulation system for hybrid WDM/FDM based fiber microstructure sensor network by using Fabry-Perot filter

Hybrid WDM/TDM enabled microstructure based optical fiber sensor network with large capacity is proposed. Assisted by Fabry-Perot filter, the demodulation system with high speed of 500Hz and high wavelength resolution less than 4.91pm is realized. © OSA 2015.

The design of a real-time nowcasting system for localised weather

National meteorological offices are largely concerned with synoptic-scale forecasting where weather predictions are produced for a whole country for 24 hours ahead. In practice, many local organisations (such as emergency services, construction industries, forestry, farming, and sports) require only local short-term, bespoke, weather predictions and warnings. This thesis shows that the less-demanding requirements do not require exceptional computing power and can be met by a modern, desk-top system which monitors site-specific ground conditions (such as temperature, pressure, wind speed and direction, etc) augmented with above ground information from satellite images to produce `nowcasts'. The emphasis in this thesis has been towards the design of such a real-time system for nowcasting. Local site-specific conditions are monitored using a custom-built, stand alone, Motorola 6809 based sub-system. Above ground information is received from the METEOSAT 4 geo-stationary satellite using a sub-system based on a commercially available equipment. The information is ephemeral and must be captured in real-time. The real-time nowcasting system for localised weather handles the data as a transparent task using the limited capabilities of the PC system. Ground data produces a time series of measurements at a specific location which represents the past-to-present atmospheric conditions of the particular site from which much information can be extracted. The novel approach adopted in this thesis is one of constructing stochastic models based on the AutoRegressive Integrated Moving Average (ARIMA) technique. The satellite images contain features (such as cloud formations) which evolve dynamically and may be subject to movement, growth, distortion, bifurcation, superposition, or elimination between images. The process of extracting a weather feature, following its motion and predicting its future evolution involves algorithms for normalisation, partitioning, filtering, image enhancement, and correlation of multi-dimensional signals in different domains. To limit the processing requirements, the analysis in this thesis concentrates on an `area of interest'. By this rationale, only a small fraction of the total image needs to be processed, leading to a major saving in time. The thesis also proposes an extention to an existing manual cloud classification technique for its implementation in automatically classifying a cloud feature over the `area of interest' for nowcasting using the multi-dimensional signals.

Extrinsic factors in the perception of bistable motion stimuli

When viewing a drifting plaid stimulus, perceived motion alternates over time between coherent pattern motion and a transparent impression of the two component gratings. It is known that changing the intrinsic attributes of such patterns (e.g. speed, orientation and spatial frequency of components) can influence percept predominance. Here, we investigate the contribution of extrinsic factors to perception; specifically contextual motion and eye movements. In the first experiment, the percept most similar to the speed and direction of surround motion increased in dominance, implying a tuned integration process. This shift primarily involved an increase in dominance durations of the consistent percept. The second experiment measured eye movements under similar conditions. Saccades were not associated with perceptual transitions, though blink rate increased around the time of a switch. This indicates that saccades do not cause switches, yet saccades in a congruent direction might help to prolong a percept because i) more saccades were directionally congruent with the currently reported percept than expected by chance, and ii) when observers were asked to make deliberate eye movements along one motion axis, this increased percept reports in that direction. Overall, we find evidence that perception of bistable motion can be modulated by information from spatially adjacent regions, and changes to the retinal image caused by blinks and saccades.

Advanced optical fibre gratings and applications

DUE TO COPYRIGHT RESTRICTIONS ONLY AVAILABLE FOR CONSULTATION AT ASTON UNIVERSITY LIBRARY AND INFORMATION SERVICES WITH PRIOR ARRANGEMENT This thesis describes a detailed study of advanced optical fibre sensors based on fibre Bragg grating (FBG), tilted fibre Bragg grating (TFBG) and long-period grating (LPG) and their applications in optical communications and sensing. The major contributions presented in this thesis are summarised below.The most important contribution from the research work presented in this thesis is the implementation of in-fibre grating based refractive index (RI) sensors, which could be the good candidates for optical biochemical sensing. Several fibre grating based RI sensors have been proposed and demonstrated by exploring novel grating structures and different fibre types, and employing efficient hydrofluoric acid etching technique to enhance the RI sensitivity. All the RI devices discussed in this thesis have been used to measure the concentration of sugar solution to simulate the chemical sensing. Efforts have also been made to overcome the RI-temperature cross-sensitivity for practical application. The demonstrated in-fibre grating based RI sensors could be further implemented as potential optical biosensors by applying bioactive coatings to realise high bio-sensitivity and bio-selectivity.Another major contribution of this thesis is the application of TFBGs. A prototype interrogation system by the use of TFBG with CCD-array was implemented to perform wavelength division multiplexing (WDM) interrogation around 800nm wavelength region with the advantages of compact size, fast detection speed and low-cost. As a high light, a novel in-fibre twist sensors utilising strong polarisation dependant coupling behaviour of an 81°-TFBG was presented to demonstrate the high torsion sensitivity and capability of direction recognition.

The mechanical and wear behaviour of B(SiC) fibre-reinforced composite materials

The mechanical properties and wear behaviour of B(SiC) fibre-reinforced metal matrix composites (MMCs) and aluminium alloy (2014) produced by metal infiltration technique were determined. Tensile tests were peliormed at different conditions on both the alloy matrix and its composite, and the tensile fracture surfaces were also examined by Scanning Electron Microscopy (SEM). Dry wear of the composite materials sliding on hardened steel was studied using a pin-on-disc type machine. The effect of fibre orientation on wear rate was studied to provide wear resistance engineering data on the MMCs. Tests were carried out with the wear surface sliding direction set normal, parallel and anti-parallel to the fibre axis. Experiments were perfonned for sliding speeds of 0.6, 1.0 and 1.6 m/s for a load range from 12 N to 60 N. A number of sensitive techniques were used to examine worn surface and debris, i.e: Scanning Electron Microscopy (SEM), Backscattered Electron Microscopy (BSEM) and X-ray Photoelectron Spectroscopy (XPS). Finally, the effect of fibre orientation on the wear rate of the Borsic-reinforced plastic matrix composites (PMCs) produced by hot pressing technique was also investigated under identical test conditions. It was found that the composite had a markedly increased tensile strength compared with the matrix. The wear results also showed that the composite exhibited extremely low wear rates compared to the matrix material and the wear rate increased with increasing sliding speed and normal load. The effect of fibre orientation was marked, the lowest wear rates were obtained by arranging the fibre perpendicular to the sliding surface, while the highest wear was obtained for the parallel orientation. The coefficient of friction was found to be lowest in the parallel orientation than the others. Wear of PMCs were influenced to the greatest extent by these test parameters although similar findings were obtained for both composites. Based on the results of analyses using SEM, BSED and XPS, possible wear mechanisms are suggested to explain the wear of these materials.

Neural network-based wind vector retrieval from satellite scatterometer data

Obtaining wind vectors over the ocean is important for weather forecasting and ocean modelling. Several satellite systems used operationally by meteorological agencies utilise scatterometers to infer wind vectors over the oceans. In this paper we present the results of using novel neural network based techniques to estimate wind vectors from such data. The problem is partitioned into estimating wind speed and wind direction. Wind speed is modelled using a multi-layer perceptron (MLP) and a sum of squares error function. Wind direction is a periodic variable and a multi-valued function for a given set of inputs; a conventional MLP fails at this task, and so we model the full periodic probability density of direction conditioned on the satellite derived inputs using a Mixture Density Network (MDN) with periodic kernel functions. A committee of the resulting MDNs is shown to improve the results.

Regularisation of mixture density networks

Mixture Density Networks are a principled method to model conditional probability density functions which are non-Gaussian. This is achieved by modelling the conditional distribution for each pattern with a Gaussian Mixture Model for which the parameters are generated by a neural network. This thesis presents a novel method to introduce regularisation in this context for the special case where the mean and variance of the spherical Gaussian Kernels in the mixtures are fixed to predetermined values. Guidelines for how these parameters can be initialised are given, and it is shown how to apply the evidence framework to mixture density networks to achieve regularisation. This also provides an objective stopping criteria that can replace the `early stopping' methods that have previously been used. If the neural network used is an RBF network with fixed centres this opens up new opportunities for improved initialisation of the network weights, which are exploited to start training relatively close to the optimum. The new method is demonstrated on two data sets. The first is a simple synthetic data set while the second is a real life data set, namely satellite scatterometer data used to infer the wind speed and wind direction near the ocean surface. For both data sets the regularisation method performs well in comparison with earlier published results. Ideas on how the constraint on the kernels may be relaxed to allow fully adaptable kernels are presented.

Neural network-based wind vector retrieval from satellite scatterometer data

Obtaining wind vectors over the ocean is important for weather forecasting and ocean modelling. Several satellite systems used operationally by meteorological agencies utilise scatterometers to infer wind vectors over the oceans. In this paper we present the results of using novel neural network based techniques to estimate wind vectors from such data. The problem is partitioned into estimating wind speed and wind direction. Wind speed is modelled using a multi-layer perceptron (MLP) and a sum of squares error function. Wind direction is a periodic variable and a multi-valued function for a given set of inputs; a conventional MLP fails at this task, and so we model the full periodic probability density of direction conditioned on the satellite derived inputs using a Mixture Density Network (MDN) with periodic kernel functions. A committee of the resulting MDNs is shown to improve the results.

The Internet and other IT resources:tools for translators within a translation programme

Information technology has increased both the speed and medium of communication between nations. It has brought the world closer, but it has also created new challenges for translation — how we think about it, how we carry it out and how we teach it. Translation and Information Technology has brought together experts in computational linguistics, machine translation, translation education, and translation studies to discuss how these new technologies work, the effect of electronic tools, such as the internet, bilingual corpora, and computer software, on translator education and the practice of translation, as well as the conceptual gaps raised by the interface of human and machine.