Pattern recognition using invariants defined from higher order spectra : 2-D image inputs

A new algorithm for extracting features from images for object recognition is described. The algorithm uses higher order spectra to provide desirable invariance properties, to provide noise immunity, and to incorporate nonlinearity into the feature extraction procedure thereby allowing the use of simple classifiers. An image can be reduced to a set of 1D functions via the Radon transform, or alternatively, the Fourier transform of each 1D projection can be obtained from a radial slice of the 2D Fourier transform of the image according to the Fourier slice theorem. A triple product of Fourier coefficients, referred to as the deterministic bispectrum, is computed for each 1D function and is integrated along radial lines in bifrequency space. Phases of the integrated bispectra are shown to be translation- and scale-invariant. Rotation invariance is achieved by a regrouping of these invariants at a constant radius followed by a second stage of invariant extraction. Rotation invariance is thus converted to translation invariance in the second step. Results using synthetic and actual images show that isolated, compact clusters are formed in feature space. These clusters are linearly separable, indicating that the nonlinearity required in the mapping from the input space to the classification space is incorporated well into the feature extraction stage. The use of higher order spectra results in good noise immunity, as verified with synthetic and real images. Classification of images using the higher order spectra-based algorithm compares favorably to classification using the method of moment invariants

Mean and variance of estimates of the bispectrum of a harmonic random process-an analysis including leakage effects

Analytical expressions are derived for the mean and variance, of estimates of the bispectrum of a real-time series assuming a cosinusoidal model. The effects of spectral leakage, inherent in discrete Fourier transform operation when the modes present in the signal have a nonintegral number of wavelengths in the record, are included in the analysis. A single phase-coupled triad of modes can cause the bispectrum to have a nonzero mean value over the entire region of computation owing to leakage. The variance of bispectral estimates in the presence of leakage has contributions from individual modes and from triads of phase-coupled modes. Time-domain windowing reduces the leakage. The theoretical expressions for the mean and variance of bispectral estimates are derived in terms of a function dependent on an arbitrary symmetric time-domain window applied to the record. the number of data, and the statistics of the phase coupling among triads of modes. The theoretical results are verified by numerical simulations for simple test cases and applied to laboratory data to examine phase coupling in a hypothesis testing framework

Position, rotation, and scale invariant recognition of images using higher-order spectra

A new approach to recognition of images using invariant features based on higher-order spectra is presented. Higher-order spectra are translation invariant because translation produces linear phase shifts which cancel. Scale and amplification invariance are satisfied by the phase of the integral of a higher-order spectrum along a radial line in higher-order frequency space because the contour of integration maps onto itself and both the real and imaginary parts are affected equally by the transformation. Rotation invariance is introduced by deriving invariants from the Radon transform of the image and using the cyclic-shift invariance property of the discrete Fourier transform magnitude. Results on synthetic and actual images show isolated, compact clusters in feature space and high classification accuracies

Assessment of retinal structure and visual function in association with diabetic peripheral neuropathy

Diabetes is an increasingly prevalent disease worldwide. Providing early management of the complications can prevent morbidity and mortality in this population. Peripheral neuropathy, a significant complication of diabetes, is the major cause of foot ulceration and amputation in diabetes. Delay in attending to complication of the disease contributes to significant medical expenses for diabetic patients and the community. Early structural changes to the neural components of the retina have been demonstrated to occur prior to the clinically visible retinal vasculature complication of diabetic retinopathy. Additionally visual functionloss has been shown to exist before the ophthalmoscopic manifestations of vasculature damage. The purpose of this thesis was to evaluate the relationship between diabetic peripheral neuropathy and both retinal structure and visual function. The key question was whether diabetic peripheral neuropathy is the potential underlying factor responsible for retinal anatomical change and visual functional loss in people with diabetes. This study was conducted on a cohort with type 2 diabetes. Retinal nerve fibre layer thickness was assessed by means of Optical Coherence Tomography (OCT). Visual function was assessed using two different methods; Standard Automated Perimetry (SAP) and flicker perimetry were performed within the central 30 degrees of fixation. The level of diabetic peripheral neuropathy (DPN) was assessed using two techniques - Quantitative Sensory Testing and Neuropathy Disability Score (NDS). These techniques are known to be capable of detecting DPN at very early stages. NDS has also been shown as a gold standard for detecting 'risk of foot ulceration'. Findings reported in this thesis showed that RNFL thickness, particularly in the inferior quadrant, has a significant association with severity of DPN when the condition has been assessed using NDS. More specifically it was observed that inferior RNFL thickness has the ability to differentiate individuals who are at higher risk of foot ulceration from those who are at lower risk, indicating that RNFL thickness can predict late-staged DPN. Investigating the association between RNFL and QST did not show any meaningful interaction, which indicates that RNFL thickness for this cohort was not as predictive of neuropathy status as NDS. In both of these studies, control participants did not have different results from the type 2 cohort who did not DPN suggesting that RNFL thickness is not a marker for diagnosing DPN at early stages. The latter finding also indicated that diabetes per se, is unlikely to affect the RNFL thickness. Visual function as measured by SAP and flicker perimetry was found to be associated with severity of peripheral neuropathy as measured by NDS. These findings were also capable of differentiating individuals at higher risk of foot ulceration; however, visual function also proved not to be a maker for early diagnosis of DPN. It was found that neither SAP, nor flicker sensitivity have meaningful associations with DPN when neuropathy status was measured using QST. Importantly diabetic retinopathy did not explain any of the findings in these experiments. The work described here is valuable as no other research to date has investigated the association between diabetic peripheral neuropathy and either retinal structure or visual function.

An ultraviolet selective photodetector based on a nanocrystalline TiO2 photoelectrochemical cell

Solar ultraviolet (UV) radiation causes a range of skin disorders as well as affecting vision and the immune system. It also inhibits development of plants and animals. UV radiation monitoring is used routinely in some locations in order to alert the population to harmful solar radiation levels. There is ongoing research to develop UV-selective-sensors [1–3]. A personal, inexpensive and simple UV-selective-sensor would be desirable to measure UV intensity exposure. A prototype of such a detector has been developed and evaluated in our laboratory. It comprises a sealed two-electrode photoelectrochemical cell (PEC) based on nanocrystalline TiO2. This abundant semiconducting oxide, which is innocuous and very sta-ble, is the subject of intense study at present due to its application in dye sensitized solar cells (DSSC) [4]. Since TiO2 has a wide band gap (EG = 3.0 eV for rutile and EG = 3.2 eV for anatase), it is inher-ently UV-selective, so that UV filters are not required. This further reduces the cost of the proposed photodetector in comparison with conventional silicon detectors. The PEC is a semiconductor–electrolyte device that generates a photovoltage when it is illuminated and a corresponding photocur-rent if the external circuit is closed. The device does not require external bias, and the short circuit current is generally a linear function of illumination intensity. This greatly simplifies the elec-trical circuit needed when using the PEC as a photodetector. DSSC technology, which is based on a PEC containing nanocrystalline TiO2 sensitized with a ruthenium dye, holds out the promise of solar cells that are significantly cheaper than traditional silicon solar cells. The UV-sensor proposed in this paper relies on the cre-ation of electron–hole pairs in the TiO2 by UV radiation, so that it would be even cheaper than a DSSC since no sensitizer dye is needed. Although TiO2 has been reported as a suitable material for UV sensing [3], to the best of our knowledge, the PEC configuration described in the present paper is a new approach. In the present study, a novel double-layer TiO2 structure has been investigated. Fabrication is based on a simple and inexpensive technique for nanostructured TiO2 deposition using microwave-activated chemical bath deposition (MW-CBD) that has been reported recently [5]. The highly transparent TiO2 (anatase) films obtained are densely packed, and they adhere very well to the transparent oxide (TCO) substrate [6]. These compact layers have been studied as contacting layers in double-layer TiO2 structures for DSSC since improvement of electron extraction at the TiO2–TCO interface is expected [7]. Here we compare devices incorporating a single mesoporous nanocrystalline TiO2 structure with devices based on a double structure in which a MW-CBD film is situated between the TCO and the mesoporous nanocrystalline TiO2 layer. Besides improving electron extraction, this film could also help to block recombination of electrons transferred to the TCO with oxidized species in the electrolyte, as has been reported in the case of DSSC for compact TiO2 films obtained by other deposition tech-niques [8,9]. The two types of UV-selective sensors were characterized in detail. The current voltage characteristics, spectral response, inten-sity dependence of short circuit current and response times were measured and analyzed in order to evaluate the potential of sealed mesoporous TiO2-based photoelectrochemical cells (PEC) as low cost personal UV-photodetectors.

Frequency response function based structural damage detection using artificial neural networks

Damage detection in structures has become increasingly important in recent years. While a number of damage detection and localization methods have been proposed, few attempts have been made to explore the structure damage with frequency response functions (FRFs). This paper illustrates the damage identification and condition assessment of a beam structure using a new frequency response functions (FRFs) based damage index and Artificial Neural Networks (ANNs). In practice, usage of all available FRF data as an input to artificial neural networks makes the training and convergence impossible. Therefore one of the data reduction techniques Principal Component Analysis (PCA) is introduced in the algorithm. In the proposed procedure, a large set of FRFs are divided into sub-sets in order to find the damage indices for different frequency points of different damage scenarios. The basic idea of this method is to establish features of damaged structure using FRFs from different measurement points of different sub-sets of intact structure. Then using these features, damage indices of different damage cases of the structure are identified after reconstructing of available FRF data using PCA. The obtained damage indices corresponding to different damage locations and severities are introduced as input variable to developed artificial neural networks. Finally, the effectiveness of the proposed method is illustrated and validated by using the finite element modal of a beam structure. The illustrated results show that the PCA based damage index is suitable and effective for structural damage detection and condition assessment of building structures.

Higher order spectral analysis of Chua's circuit

Higher order spectral analysis is used to investigate nonlinearities in time series of voltages measured from a realization of Chua's circuit. For period-doubled limit cycles, quadratic and cubic nonlinear interactions result in phase coupling and energy exchange between increasing numbers of triads and quartets of Fourier components as the nonlinearity of the system is increased. For circuit parameters that result in a chaotic Rossler-type attractor, bicoherence and tricoherence spectra indicate that both quadratic and cubic nonlinear interactions are important to the dynamics. When the circuit exhibits a double-scroll chaotic attractor the bispectrum is zero, but the tricoherences are high, consistent with the importance of higher-than-second order nonlinear interactions during chaos associated with the double scroll.

Higher-order spectral analysis of nonlinear ocean surface gravity waves

Higher-order spectral analysis is used to detect the presence of secondary and tertiary forced waves associated with the nonlinearity of energetic swell observed in 8- and 13-m water depths. Higher-order spectral analysis techniques are first described and then applied to the field data, followed by a summary of the results.

Instantaneous phase of the autocorrelation and robustness to signal-dependent noise

The phase of an analytic signal constructed from the autocorrelation function of a signal contains significant information about the shape of the signal. Using Bedrosian's (1963) theorem for the Hilbert transform it is proved that this phase is robust to multiplicative noise if the signal is baseband and the spectra of the signal and the noise do not overlap. Higher-order spectral features are interpreted in this context and shown to extract nonlinear phase information while retaining robustness. The significance of the result is that prior knowledge of the spectra is not required.

On the behaviour of higher-order spectral features for object recognition in the presence of various types of noise

This paper presents results on the robustness of higher-order spectral features to Gaussian, Rayleigh, and uniform distributed noise. Based on cluster plots and accuracy results for various signal to noise conditions, the higher-order spectral features are shown to be better than moment invariant features.

Effect of accommodation on peripheral ocular aberrations

Changes in peripheral aberrations, particularly higher-order aberrations, as a function of accommodation have received little attention. Wavefront aberrations were measured for the right eyes of 9 young adult emmetropes at 38 field positions in the central 42 x 32 degrees of the visual field. Subjects accommodated monocularly to targets at vergences of either 0.3 or 4.0 D. Wavefront data for a 5 mm diameter pupil were analyzed either in terms of the vector components of refraction or Zernike coefficients and total RMS wavefront aberrations. Relative peripheral refractive error (RPRE) was myopic at both accommodation demands and showed only a slight, not statistically significant, hypermetropic shift in the vertical meridian with the higher accommodation demand. There was little change in the astigmatic components of refraction or the higher-order Zernike coefficients, apart from fourth-order spherical aberration which became more negative (by 0.10 µm) at all field locations. Although it has been suggested that nearwork and the state of peripheral refraction may play some role in myopia development, for most of our adult emmetropes any changes with accommodation in RPRE and aberration were small. Hence it seems unlikely that such changes can be of importance to late-onset myopisation.

Extending client-centered support : counselors’ proposals to shift from email to telephone counseling

The availability and use of online counseling approaches has increased rapidly over the last decade. While research has suggested a range of potential affordances and limitations of online counseling modalities, very few studies have offered detailed examinations of how counselors and clients manage asynchronous email counseling exchanges. In this paper we examine email exchanges involving clients and counselors through Kids Helpline, a national Australian counseling service that offers free online, email and telephone counseling for young people up to the age of 25. We employ tools from the traditions of ethnomethodology and conversation analysis to analyze the ways in which counselors from Kids Helpline request that their clients call them, and hence change the modality of their counseling relationship, from email to telephone counseling. This paper shows the counselors’ three multi-layered approaches in these emails as they negotiate the potentially delicate task of requesting and persuading a client to change the trajectory of their counseling relationship from text to talk without placing that relationship in jeopardy.

An exploration of young students' ability to generalise function tasks

The Early Years Generalising Project involves Australian students, Years 1-4 (age 5-9), and explores how the students grasp and express generalisations. This paper focuses on the data collected from clinical interviews with Year 3 and 4 cohorts in an investigative study focusing on the identifications, prediction and justification of function rules. It reports on students' attempts to generalise from function machine contexts, describing the various ways students express generalisation and highlighting the different levels of justification given by students. Finally, we conjecture that there are a set of stages in the expression and justification of generalisations that assist students to reach generality within tasks.

Enhancing workplace learning through collaborative HRD

Human resource development (HRD) has evolved a great deal over the past 20 years. Indeed, developments in HRD theory, research and practice have helped transform HRD from a reactive function focusing on administrative and bureaucratic issues to a proactive function focusing on creating learning and development opportunities for employees that not only allow them to achieve their potential but also make a substantial contribution to the longterm survival and sustainability of the organisation. HRD is now seen as an investment in the future of an organisation. This investment perspective is based on the recognition that HRD is linked to business strategy and the achievement of competitive advantage (Caravan et al. 2002). One reason for the shift in emphasis is that many of the traditional sources of competitive advantage (technology, economies of scale) have diminished in value. Nowadays it is the workforce that has come to be seen as an important source of competitive advantage for the organisation. However, not too long ago employees were viewed by management as a disposable resource rather than an asset to an organisation.