Context-Based Modelling of Interferometric Signals for the Assessment of Tear-Film Suface Quality

Modelling of interferometric signals related to tear film surface quality is considered. In the context of tear film surface quality estimation in normal healthy eyes, two clinical parameters are of interest: the build-up time, and the average interblink surface quality. The former is closely related to the signal derivative while the latter to the signal itself. Polynomial signal models, chosen for a particular set of noisy interferometric measurements, can be optimally selected, in some sense, with a range of information criteria such as AIC, MDL, Cp, and CME. Those criteria, however, do not always guarantee that the true derivative of the signal is accurately represented and they often overestimate it. Here, a practical method for judicious selection of model order in a polynomial fitting to a signal is proposed so that the derivative of the signal is adequately represented. The paper highlights the importance of context-based signal modelling in model order selection.

Analysis of phasor measurement method in tracking the power frequency of distorted signals

This paper presents an analysis of phasor measurement method for tracking the fundamental power frequency to show if it has the performance necessary to cope with the requirements of power system protection and control. In this regard, several computer simulations presenting the conditions of a typical power system signal especially those highly distorted by harmonics, noise and offset, are provided to evaluate the response of the Phasor Measurement (PM) technique. A new method, which can shorten the delay of estimation, has also been proposed for the PM method to work for signals free of even-order harmonics.

Destination brand equity among the host community : a potential source of comparative advantage for DMO's

Since the emergence of the destination branding literature in 1998, there have been few studies related to performance measurement of destination brand campaigns. There has also been little interest to date in researching the extent to which a destination brand represents the host community’s sense of place. Given that local residents represent a key stakeholder group for the destination marketing organisation (DMO), research is required to examine the extent to which marketing communications have been effective in enhancing engagement with the brand, and inducing a brand image that is congruent with the brand identity. Motivated by conceptual and practical aims, this paper reports the trial of a hierarchy of consumer-based brand equity (CBBE) for a destination, from the perspective of residents as active participants of local tourism. It is proposed that strong levels of CBBE among the host community representsa strong level of CBBE among the host community represents a source of comparative advantage for a destination, for which the DMO could proactively develop into a competitive advantage.

Peak-to-average power ratio of IEEE 802.11a PHY layer signals

In this chapter we propose clipping with amplitude and phase corrections to reduce the peak-to-average power ratio (PAR) of orthogonal frequency division multiplexed (OFDM) signals in high-speed wireless local area networks defined in IEEE 802.11a physical layer. The proposed techniques can be implemented with a small modification at the transmitter and the receiver remains standard compliant. PAR reduction as much as 4dB can be achieved by selecting a suitable clipping ratio and a correction factor depending on the constellation used. Out of band noise (OBN) is also reduced.

Performance analysis of adaptive lattice filters for FM signals and alpha-stable processes

The performance of an adaptive filter may be studied through the behaviour of the optimal and adaptive coefficients in a given environment. This thesis investigates the performance of finite impulse response adaptive lattice filters for two classes of input signals: (a) frequency modulated signals with polynomial phases of order p in complex Gaussian white noise (as nonstationary signals), and (b) the impulsive autoregressive processes with alpha-stable distributions (as non-Gaussian signals). Initially, an overview is given for linear prediction and adaptive filtering. The convergence and tracking properties of the stochastic gradient algorithms are discussed for stationary and nonstationary input signals. It is explained that the stochastic gradient lattice algorithm has many advantages over the least-mean square algorithm. Some of these advantages are having a modular structure, easy-guaranteed stability, less sensitivity to the eigenvalue spread of the input autocorrelation matrix, and easy quantization of filter coefficients (normally called reflection coefficients). We then characterize the performance of the stochastic gradient lattice algorithm for the frequency modulated signals through the optimal and adaptive lattice reflection coefficients. This is a difficult task due to the nonlinear dependence of the adaptive reflection coefficients on the preceding stages and the input signal. To ease the derivations, we assume that reflection coefficients of each stage are independent of the inputs to that stage. Then the optimal lattice filter is derived for the frequency modulated signals. This is performed by computing the optimal values of residual errors, reflection coefficients, and recovery errors. Next, we show the tracking behaviour of adaptive reflection coefficients for frequency modulated signals. This is carried out by computing the tracking model of these coefficients for the stochastic gradient lattice algorithm in average. The second-order convergence of the adaptive coefficients is investigated by modeling the theoretical asymptotic variance of the gradient noise at each stage. The accuracy of the analytical results is verified by computer simulations. Using the previous analytical results, we show a new property, the polynomial order reducing property of adaptive lattice filters. This property may be used to reduce the order of the polynomial phase of input frequency modulated signals. Considering two examples, we show how this property may be used in processing frequency modulated signals. In the first example, a detection procedure in carried out on a frequency modulated signal with a second-order polynomial phase in complex Gaussian white noise. We showed that using this technique a better probability of detection is obtained for the reduced-order phase signals compared to that of the traditional energy detector. Also, it is empirically shown that the distribution of the gradient noise in the first adaptive reflection coefficients approximates the Gaussian law. In the second example, the instantaneous frequency of the same observed signal is estimated. We show that by using this technique a lower mean square error is achieved for the estimated frequencies at high signal-to-noise ratios in comparison to that of the adaptive line enhancer. The performance of adaptive lattice filters is then investigated for the second type of input signals, i.e., impulsive autoregressive processes with alpha-stable distributions . The concept of alpha-stable distributions is first introduced. We discuss that the stochastic gradient algorithm which performs desirable results for finite variance input signals (like frequency modulated signals in noise) does not perform a fast convergence for infinite variance stable processes (due to using the minimum mean-square error criterion). To deal with such problems, the concept of minimum dispersion criterion, fractional lower order moments, and recently-developed algorithms for stable processes are introduced. We then study the possibility of using the lattice structure for impulsive stable processes. Accordingly, two new algorithms including the least-mean P-norm lattice algorithm and its normalized version are proposed for lattice filters based on the fractional lower order moments. Simulation results show that using the proposed algorithms, faster convergence speeds are achieved for parameters estimation of autoregressive stable processes with low to moderate degrees of impulsiveness in comparison to many other algorithms. Also, we discuss the effect of impulsiveness of stable processes on generating some misalignment between the estimated parameters and the true values. Due to the infinite variance of stable processes, the performance of the proposed algorithms is only investigated using extensive computer simulations.

Coding speech signals at very low rates (below 1 kb/s) with high intelligibility

This thesis presents an original approach to parametric speech coding at rates below 1 kbitsjsec, primarily for speech storage applications. Essential processes considered in this research encompass efficient characterization of evolutionary configuration of vocal tract to follow phonemic features with high fidelity, representation of speech excitation using minimal parameters with minor degradation in naturalness of synthesized speech, and finally, quantization of resulting parameters at the nominated rates. For encoding speech spectral features, a new method relying on Temporal Decomposition (TD) is developed which efficiently compresses spectral information through interpolation between most steady points over time trajectories of spectral parameters using a new basis function. The compression ratio provided by the method is independent of the updating rate of the feature vectors, hence allows high resolution in tracking significant temporal variations of speech formants with no effect on the spectral data rate. Accordingly, regardless of the quantization technique employed, the method yields a high compression ratio without sacrificing speech intelligibility. Several new techniques for improving performance of the interpolation of spectral parameters through phonetically-based analysis are proposed and implemented in this research, comprising event approximated TD, near-optimal shaping event approximating functions, efficient speech parametrization for TD on the basis of an extensive investigation originally reported in this thesis, and a hierarchical error minimization algorithm for decomposition of feature parameters which significantly reduces the complexity of the interpolation process. Speech excitation in this work is characterized based on a novel Multi-Band Excitation paradigm which accurately determines the harmonic structure in the LPC (linear predictive coding) residual spectra, within individual bands, using the concept 11 of Instantaneous Frequency (IF) estimation in frequency domain. The model yields aneffective two-band approximation to excitation and computes pitch and voicing with high accuracy as well. New methods for interpolative coding of pitch and gain contours are also developed in this thesis. For pitch, relying on the correlation between phonetic evolution and pitch variations during voiced speech segments, TD is employed to interpolate the pitch contour between critical points introduced by event centroids. This compresses pitch contour in the ratio of about 1/10 with negligible error. To approximate gain contour, a set of uniformly-distributed Gaussian event-like functions is used which reduces the amount of gain information to about 1/6 with acceptable accuracy. The thesis also addresses a new quantization method applied to spectral features on the basis of statistical properties and spectral sensitivity of spectral parameters extracted from TD-based analysis. The experimental results show that good quality speech, comparable to that of conventional coders at rates over 2 kbits/sec, can be achieved at rates 650-990 bits/sec.

Pathogenicity of Plesiomonas shigelloides : interactions with eukaryotic host cells in vitro

Diarrhoea is one of the leading causes of morbidity and mortality in populations in developing countries and is a significant health issue throughout the world. Despite the frequency and the severity of the diarrhoeal disease, mechanisms of pathogenesis for many of the causative agents have been poorly characterised. Although implicated in a number of intestinal and extra-intestinal infections in humans, Plesiomonas shigelloides generally has been dismissed as an enteropathogen due to the lack of clearly demonstrated virulence-associated properties such as production of cytotoxins and enterotoxins or invasive abilities. However, evidence from a number of sources has indicated that this species may be the cause of a number of clinical infections. The work described in this thesis seeks to resolve this discrepancy by investigating the pathogenic potential of P. shigelloides using in vitro cell models. The focus of this research centres on how this organism interacts with human host cells in an experimental model. Very little is known about the pathogenic potential of P. shigel/oides and its mechanisms in human infections and disease. However, disease manifestations mimic those of other related microorganisms. Chapter 2 reviews microbial pathogenesis in general, with an emphasis on understanding the mechanisms resulting from infection with bacterial pathogens and the alterations in host cell biology. In addition, this review analyses the pathogenic status of a poorly-defined enteropathogen, P. shigelloides. Key stages of pathogenicity must occur in order for a bacterial pathogen to cause disease. Such stages include bacterial adherence to host tissue, bacterial entry into host tissues (usually required), multiplication within host tissues, evasion of host defence mechanisms and the causation of damage. In this study, these key strategies in infection and disease were sought to help assess the pathogenic potential of P. shigelloides (Chapter 3). Twelve isolates of P. shigelloides, obtained from clinical cases of gastroenteritis, were used to infect monolayers of human intestinal epithelial cells in vitro. Ultrastructural analysis demonstrated that P. shigelloides was able to adhere to the microvilli at the apical surface of the epithelial cells and also to the plasma membranes of both apical and basal surfaces. Furthermore, it was demonstrated that these isolates were able to enter intestinal epithelial cells. Internalised bacteria often were confined within vacuoles surrounded by single or multiple membranes. Observation of bacteria within membranebound vacuoles suggests that uptake of P. shigelloides into intestinal epithelial cells occurs via a process morphologically comparable to phagocytosis. Bacterial cells also were observed free in the host cell cytoplasm, indicating that P. shige/loides is able to escape from the surrounding vacuolar membrane and exist within the cytosol of the host. Plesiomonas shigelloides has not only been implicated in gastrointestinal infections, but also in a range of non-intestinal infections such as cholecystitis, proctitis, septicaemia and meningitis. The mechanisms by which P. shigelloides causes these infections are not understood. Previous research was unable to ascertain the pathogenic potential of P. shigel/oides using cells of non-intestinal origin (HEp-2 cells derived from a human larynx carcinoma and Hela cells derived from a cervical carcinoma). However, with the recent findings (from this study) that P. shigelloides can adhere to and enter intestinal cells, it was hypothesised, that P. shigel/oides would be able to enter Hela and HEp-2 cells. Six clinical isolates of P. shigelloides, which previously have been shown to be invasive to intestinally derived Caco-2 cells (Chapter 3) were used to study interactions with Hela and HEp-2 cells (Chapter 4). These isolates were shown to adhere to and enter both nonintestinal host cell lines. Plesiomonas shigelloides were observed within vacuoles surrounded by single and multiple membranes, as well as free in the host cell cytosol, similar to infection by P. shigelloides of Caco-2 cells. Comparisons of the number of bacteria adhered to and present intracellularly within Hela, HEp-2 and Caco-2 cells revealed a preference of P. shigelloides for Caco-2 cells. This study conclusively showed for the first time that P. shigelloides is able to enter HEp-2 and Hela cells, demonstrating the potential ability to cause an infection and/or disease of extra-intestinal sites in humans. Further high resolution ultrastructural analysis of the mechanisms involved in P. shigelloides adherence to intestinal epithelial cells (Chapter 5) revealed numerous prominent surface features which appeared to be involved in the binding of P. shige/loides to host cells. These surface structures varied in morphology from small bumps across the bacterial cell surface to much longer filaments. Evidence that flagella might play a role in bacterial adherence also was found. The hypothesis that filamentous appendages are morphologically expressed when in contact with host cells also was tested. Observations of bacteria free in the host cell cytosol suggests that P. shigelloides is able to lyse free from the initial vacuolar compartment. The vacuoles containing P. shigel/oides within host cells have not been characterised and the point at which P. shigelloides escapes from the surrounding vacuolar compartment has not been determined. A cytochemical detection assay for acid phosphatase, an enzymatic marker for lysosomes, was used to analyse the co-localisation of bacteria-containing vacuoles and acid phosphatase activity (Chapter 6). Acid phosphatase activity was not detected in these bacteria-containing vacuoles. However, the surface of many intracellular and extracellular bacteria demonstrated high levels of acid phosphatase activity, leading to the proposal of a new virulence factor for P. shigelloides. For many pathogens, the efficiency with which they adhere to and enter host cells is dependant upon the bacterial phase of growth. Such dependency reflects the timing of expression of particular virulence factors important for bacterial pathogenesis. In previous studies (Chapter 3 to Chapter 6), an overnight culture of P. shigelloides was used to investigate a number of interactions, however, it was unknown whether this allowed expression of bacterial factors to permit efficient P. shigelloides attachment and entry into human cells. In this study (Chapter 7), a number of clinical and environmental P. shigelloides isolates were investigated to determine whether adherence and entry into host cells in vitro was more efficient during exponential-phase or stationary-phase bacterial growth. An increase in the number of adherent and intracellular bacteria was demonstrated when bacteria were inoculated into host cell cultures in exponential phase cultures. This was demonstrated clearly for 3 out of 4 isolates examined. In addition, an increase in the morphological expression of filamentous appendages, a suggested virulence factor for P. shigel/oides, was observed for bacteria in exponential growth phase. These observations suggest that virulence determinants for P. shigel/oides may be more efficiently expressed when bacteria are in exponential growth phase. This study demonstrated also, for the first time, that environmental water isolates of P. shigelloides were able to adhere to and enter human intestinal cells in vitro. These isolates were seen to enter Caco-2 host cells through a process comparable to the clinical isolates examined. These findings support the hypothesis of a water transmission route for P. shigelloides infections. The results presented in this thesis contribute significantly to our understanding of the pathogenic mechanisms involved in P. shigelloides infections and disease. Several of the factors involved in P. shigelloides pathogenesis have homologues in other pathogens of the human intestine, namely Vibrio, Aeromonas, Salmonella, Shigella species and diarrhoeaassociated strains of Escherichia coli. This study emphasises the relevance of research into Plesiomonas as a means of furthering our understanding of bacterial virulence in general. As well it provides tantalising clues on normal and pathogenic host cell mechanisms.

Statistical modeling to determine resonant frequency information present in combustion chamber pressure signals

A statistical modeling method to accurately determine combustion chamber resonance is proposed and demonstrated. This method utilises Markov-chain Monte Carlo (MCMC) through the use of the Metropolis-Hastings (MH) algorithm to yield a probability density function for the combustion chamber frequency and find the best estimate of the resonant frequency, along with uncertainty. The accurate determination of combustion chamber resonance is then used to investigate various engine phenomena, with appropriate uncertainty, for a range of engine cycles. It is shown that, when operating on various ethanol/diesel fuel combinations, a 20% substitution yields the least amount of inter-cycle variability, in relation to combustion chamber resonance.