The influence of dopamine on semantic activation in Parkinson's disease: Evidence from a multipriming task

Research has suggested that semantic processing deficits in Parkinson's disease (PD) are related to striatal dopamine deficiency. As an investigation of the influence of dopamine on semantic activation in PD, 7 participants with PD performed a lexical-decision task when on and off levodopa medication. Seven healthy controls matched to the participants with PD in terms of sex, age, and education also participated in the study. By use of a multipriming paradigm, whereby 2 prime words were presented prior to the target word, semantic priming effects were measured across stimulus onset asynchronies (SOAs) of 250 Ins and 1,200 Ins. The results revealed a similar pattern of priming across SOAs for the control group and the PD participants on medication. In contrast, within-group comparisons revealed that automatic semantic activation was compromised in PD participants when off medication. The implications of these results for the neuromodulatory influence of dopamine on semantic processing in PD are discussed.

Novel ultra-wideband pulse spectrum modulation scheme

Current ultra-wideband communication systems use short narrow timed pulse sequences to transmit information. Some disadvantages of UWB communication systems are its interference of other conventional wireless systems and its reliance on time hopping schemes for multiple access. This paper presents a novel UWB data modulation scheme based on pulse shaping. This modulation scheme adds more flexibility for data modulation in UWB communication systems. The modulation scheme encodes data in both the timing and frequency spectrum of the transmitted pulse. This has the potential to improve data throughput rates and to lower interference between UWB and narrowband systems.

Retrieving designs from a sketch using an automated GT coding and classification system

While the retrieval of existing designs to prevent unnecessary duplication of parts is a recognised strategy in the control of design costs the available techniques to achieve this, even in product data management systems, are limited in performance or require large resources. A novel system has been developed based on a new version of an existing coding system (CAMAC) that allows automatic coding of engineering drawings and their subsequent retrieval using a drawing of the desired component as the input. The ability to find designs using a detail drawing rather than textual descriptions is a significant achievement in itself. Previous testing of the system has demonstrated this capability but if a means could be found to find parts from a simple sketch then its practical application would be much more effective. This paper describes the development and testing of such a search capability using a database of over 3000 engineering components.

Exploitation of fibre characteristics in temperature sensing and radio-over-fibre applications

The development of sensing devices is one of the instrumentation fields that has grown rapidly in the last decade. Corresponding to the swift advance in the development of microelectronic sensors, optical fibre sensors are widely investigated because of their advantageous properties over the electronics sensors such as their wavelength multiplexing capability and high sensitivity to temperature, pressure, strain, vibration and acoustic emission. Moreover, optical fibre sensors are more attractive than the electronics sensors as they can perform distributed sensing, in terms of covering a reasonably large area using a single piece of fibre. Apart from being a responsive element in the sensing field, optical fibre possesses good assets in generating, distributing, processing and transmitting signals in the future broadband information network. These assets include wide bandwidth, high capacity and low loss that grant mobility and flexibility for wireless access systems. Among these core technologies, the fibre optic signal processing and transmission of optical and radio frequency signals have been the subjects of study in this thesis. Based on the intrinsic properties of single-mode optical fibre, this thesis aims to exploit the fibre characteristics such as thermal sensitivity, birefringence, dispersion and nonlinearity, in the applications of temperature sensing and radio-over-fibre systems. By exploiting the fibre thermal sensitivity, a fully distributed temperature sensing system consisting of an apodised chirped fibre Bragg grating has been implemented. The proposed system has proven to be efficient in characterising grating and providing the information of temperature variation, location and width of the heat source applied in the area under test.To exploit the fibre birefringence, a fibre delay line filter using a single high-birefringence optical fibre structure has been presented. The proposed filter can be reconfigured and programmed by adjusting the input azimuth of launched light, as well as the strength and direction of the applied coupling, to meet the requirements of signal processing for different purposes in microwave photonic and optical filtering applications. To exploit the fibre dispersion and nonlinearity, experimental investigations have been carried out to study their joint effect in high power double-sideband and single-sideband modulated links with the presence of fibre loss. The experimental results have been theoretically verified based on the in-house implementation of the split-step Fourier method applied to the generalised nonlinear Schrödinger equation. Further simulation study on the inter-modulation distortion in two-tone signal transmission has also been presented so as to show the effect of nonlinearity of one channel on the other. In addition to the experimental work, numerical simulations have also been carried out in all the proposed systems, to ensure that all the aspects concerned are comprehensively investigated.

Low bit-rate speech encoding for digital mobile radio

The need for low bit-rate speech coding is the result of growing demand on the available radio bandwidth for mobile communications both for military purposes and for the public sector. To meet this growing demand it is required that the available bandwidth be utilized in the most economic way to accommodate more services. Two low bit-rate speech coders have been built and tested in this project. The two coders combine predictive coding with delta modulation, a property which enables them to achieve simultaneously the low bit-rate and good speech quality requirements. To enhance their efficiency, the predictor coefficients and the quantizer step size are updated periodically in each coder. This enables the coders to keep up with changes in the characteristics of the speech signal with time and with changes in the dynamic range of the speech waveform. However, the two coders differ in the method of updating their predictor coefficients. One updates the coefficients once every one hundred sampling periods and extracts the coefficients from input speech samples. This is known in this project as the Forward Adaptive Coder. Since the coefficients are extracted from input speech samples, these must be transmitted to the receiver to reconstruct the transmitted speech sample, thus adding to the transmission bit rate. The other updates its coefficients every sampling period, based on information of output data. This coder is known as the Backward Adaptive Coder. Results of subjective tests showed both coders to be reasonably robust to quantization noise. Both were graded quite good, with the Forward Adaptive performing slightly better, but with a slightly higher transmission bit rate for the same speech quality, than its Backward counterpart. The coders yielded acceptable speech quality of 9.6kbps for the Forward Adaptive and 8kbps for the Backward Adaptive.

The application of methods of uncertain reasoning to the biological classification of river water quality

This thesis presents an investigation into the application of methods of uncertain reasoning to the biological classification of river water quality. Existing biological methods for reporting river water quality are critically evaluated, and the adoption of a discrete biological classification scheme advocated. Reasoning methods for managing uncertainty are explained, in which the Bayesian and Dempster-Shafer calculi are cited as primary numerical schemes. Elicitation of qualitative knowledge on benthic invertebrates is described. The specificity of benthic response to changes in water quality leads to the adoption of a sensor model of data interpretation, in which a reference set of taxa provide probabilistic support for the biological classes. The significance of sensor states, including that of absence, is shown. Novel techniques of directly eliciting the required uncertainty measures are presented. Bayesian and Dempster-Shafer calculi were used to combine the evidence provided by the sensors. The performance of these automatic classifiers was compared with the expert's own discrete classification of sampled sites. Variations of sensor data weighting, combination order and belief representation were examined for their effect on classification performance. The behaviour of the calculi under evidential conflict and alternative combination rules was investigated. Small variations in evidential weight and the inclusion of evidence from sensors absent from a sample improved classification performance of Bayesian belief and support for singleton hypotheses. For simple support, inclusion of absent evidence decreased classification rate. The performance of Dempster-Shafer classification using consonant belief functions was comparable to Bayesian and singleton belief. Recommendations are made for further work in biological classification using uncertain reasoning methods, including the combination of multiple-expert opinion, the use of Bayesian networks, and the integration of classification software within a decision support system for water quality assessment.