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

A general procedure for the derivation of principal domains of higher-order spectra

A general procedure to determine the principal domain (i.e., nonredundant region of computation) of any higher-order spectrum is presented, using the bispectrum as an example. The procedure is then applied to derive the principal domain of the trispectrum of a real-valued, stationary time series. These results are easily extended to compute the principal domains of other higher-order spectra

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

Scaling analysis of the unsteady natural convection boundary layer adjacent to an inclined plate for Pr > 1 following instantaneous heating

The unsteady natural convection boundary layer adjacent to an instantaneously heated inclined plate is investigated using an improved scaling analysis and direct numerical simulations. The development of the unsteady natural convection boundary layer following instantaneous heating may be classified into three distinct stages including a start-up stage, a transitional stage and a steady state stage, which can be clearly identified in the analytical and numerical results. Major scaling relations of the velocity and thicknesses and the flow development time of the natural convection boundary layer are obtained using triple-layer integral solutions and verified by direct numerical simulations over a wide range of flow parameters.

Application of machine learning in fault diagnostics of mechanical systems

A diagnostic method based on Bayesian Networks (probabilistic graphical models) is presented. Unlike conventional diagnostic approaches, in this method instead of focusing on system residuals at one or a few operating points, diagnosis is done by analyzing system behavior patterns over a window of operation. It is shown how this approach can loosen the dependency of diagnostic methods on precise system modeling while maintaining the desired characteristics of fault detection and diagnosis (FDD) tools (fault isolation, robustness, adaptability, and scalability) at a satisfactory level. As an example, the method is applied to fault diagnosis in HVAC systems, an area with considerable modeling and sensor network constraints.

An ecological footprint for an early learning centre : identifying opportunities for early childhood sustainability education through interdisciplinary research

In this study, engineers and educators worked together to adapt and apply the ecological footprint (EF) methodology to an early learning centre in Brisbane, Australia. Results were analysed to determine how environmental impact can be reduced at the study site and more generally across early childhood settings. It was found that food, transport and energy consumption had the largest impact on the centre’s overall footprint. In transport and energy, early childhood centres can reduce their impact through infrastructure and cultural change, in association with changed curriculum strategies. Building design, the type of energy purchased and appliance usage can all be modified to reduce the energy footprint. The transport footprint can be reduced through more families using active and public transport, which can be encouraged by providing information, support and facilities and appropriate siting of new centres. Introducing the concept of ecological footprint in early childhood education may be an effective way to educate children, staff and parents on the links between the food they eat, land usage and environmental impact. This study responds directly to the call in this journal for research focused on early childhood education and for more to be made of interdisciplinary research opportunities.

Crisis preparedness of construction companies

In high-risk industries, companies with well-conceived crisis management plans are at a commercial advantage. While there is some understanding of the risk management practices of construction companies, there is little insight into their crisis preparedness. This paper presents the findings of exploratory research that investigated this issue. Using a diagnostic model of crisis preparedness that has been developed and tested across a broad range of industries, it concludes that if the sample surveyed is typical, then corporate philosophies in construction companies do not support crisis management activities. Furthermore, crisis planning is rudimentary and undertaken in an insular, informal, fragmented fashion, supported by few resources and little strategic guidance. Consequently, many construction companies will have an inadequate understanding of their crisis exposure, of how to cope with crises when they happen, and of how to learn and recover from their aftermath.

Hypothetical model of hydrophilic lubrication in synovial joints

This paper presents a new insight into the mechanism of biolubrication of articulating mammalian joints that includes the function of surface-active phospholipids (SAPLs). SAPLs can be adsorbed on surface of cartilage membranes as a hydrophobic monolayer (H-phobic-M Madel or Hills' Model) or as a newly proposed hydrophilic bilayer (H-philic-B Model). With respect to the synovial joint's frictionless work, three processes are identified namely: monolayer/bilayer phospholipids binding to cartilage with lubricin interaction; influence of induced-pressure on interaction of hyaluronan with phospholipids; and biolubrication arising from two gliding articular hydrophilic surfaces acting as reverse micelle. Lubricin is considered to play critical role as a supplier of phospholipids, which overlay the articular surface of articular cartilage. Hyaluronic acid is considered to play a critical mediating role in the interaction between the hydrophilic part of phospholipids, the articular surface and water (hydration) in facilitating the lubrication process. Tivo models of frictionless lubrication processes, namely hydrophobic (H-phobic-M Model) and our conceptual hydrophilic (H-philic-B Model), are compared. © Institution of Engineers Australia, 2008.