Spectral kernels for classification

Spectral methods, as an unsupervised technique, have been used with success in data mining such as LSI in information retrieval, HITS and PageRank in Web search engines, and spectral clustering in machine learning. The essence of success in these applications is the spectral information that captures the semantics inherent in the large amount of data required during unsupervised learning. In this paper, we ask if spectral methods can also be used in supervised learning, e.g., classification. In an attempt to answer this question, our research reveals a novel kernel in which spectral clustering information can be easily exploited and extended to new incoming data during classification tasks. From our experimental results, the proposed Spectral Kernel has proved to speedup classification tasks without compromising accuracy.

Tests of measurement invariance failed to support the application of the "then-test"

Objective
The use of then-test (retrospective pre-test) scores has frequently been proposed as a solution to potential confounding of change scores because of response shift, as it is assumed that then-test and post-test responses are provided from the same perspective. However, this assumption has not been formally tested using robust quantitative methods. The aim of this study was to compare the psychometric performance of then-test/post-test with traditional pre-test/post-test data and assessing whether the resulting data structures support the application of the then-test for evaluations of chronic disease self-management interventions.

Study Design and Setting
Pre-test, post-test, and then-test data were collected from 314 participants of self-management courses using the Health Education Impact Questionnaire (heiQ). The derived change scores (pre-test/post-test; then-test/post-test) were examined for their psychometric performance using tests of measurement invariance.

Results
Few questionnaire items were noninvariant across pre-test/post-test, with four items identified and requiring removal to enable an unbiased comparison of factor means. In contrast, 12 items were identified and required removal in then-test/post-test data to avoid biased change score estimates.

Conclusion
Traditional pre-test/post-test data appear to be robust with little indication of response shift. In contrast, the weaker psychometric performance of then-test/post-test data suggests psychometric flaws that may be the result of implicit theory of change, social desirability, and recall bias.

Use of high resolution digital multi-spectral imagery to assess the distribution of disease caused by Phytophthora cinnamomi on heathland at Anglesea, Victoria

Disease caused by the soilborne plant pathogen Phytophthora cinnamomi causes long-term floristic and structural changes in native vegetation communities in Australia. Key components of the management of this disease are to know where it occurs and the rate at which it spreads. The distribution of P. cinnamomi has generally been assessed as locality points of infestation and mapping the extent of diseased vegetation in any area is difficult and costly. This study was undertaken in P. cinnamomi-infested heathland communities in southern Victoria, Australia, where the symptoms of P. cinnamomi arise as a mosaic within healthy vegetation. We investigated the potential to improve the efficiency and effectiveness of mapping and monitoring vegetation affected by P. cinnamomi using digital multi-spectral imaging. This technique was developed for the purposes of monitoring vegetation and provides a single, seamless ortho-rectified digital image over the total area of interest. It is used to spatially quantify small differences in the characteristics of vegetation. In this study, the symptoms of disease caused by P. cinnamomi infestation were related to differences in the imagery and were used to map areas of infestation. Comparison of the digital multi-spectral imaging indications with on-ground observations gave moderate accuracy between the datasets (κ = 0.49) for disease and healthy indications. This study demonstrates the ability of the technique to determine disease extent over broad areas in native vegetation and provides a non-invasive, cost effective tool for management.

Semi-hyperbolic mappings in Banach spaces

The definition of semi-hyperbolic dynamical systems generated by Lipschitz continuous and not necessarily invertible mappings in Banach spaces is presented in this thesis. Like hyperbolic mappings, they involve a splitting into stable and unstable spaces, but a slight leakage from the strict invariance of the spaces is possible and the unstable subspaces are assumed to be finite dimensional. Bi-shadowing is a combination of the concepts of shadowing and inverse shadowing and is usually used to compare pseudo-trajectories calculated by a computer with the true trajectories. In this thesis, the concept of bi-shadowing in a Banach space is defined and proved for semi-hyperbolic dynamical systems generated by Lipschitz mappings. As an application to the concept of bishadowing, linear delay differential equations are shown to be bi-shadowing with respect to pseudo-trajectories generated by nonlinear small perturbations of the linear delay equation. This shows robustness of solutions of the linear delay equation with respect to small nonlinear perturbations. Complicated dynamical behaviour is often a consequence of the expansivity of a dynamical system. Semi-hyperbolic dynamical systems generated by Lipschitz mappings on a Banach space are shown to be exponentially expansive, and explicit rates of expansion are determined. The result is applied to a nonsmooth noninvertible system generated by delay differential equation. It is shown that semi-hyperbolic mappings are locally φ-contracting, where -0 is the Hausdorff measure of noncompactness, and that a linear operator is semi-hyperbolic if and only if it is φ-contracting and has no spectral values on the unit circle. The definition of φ-bi-shadowing is given and it is shown that semi-hyperbolic mappings in Banach spaces are φ-bi-shadowing with respect to locally condensing continuous comparison mappings. The result is applied to linear delay differential equations of neutral type with nonsmooth perturbations. Finally, it is shown that a small delay perturbation of an ordinary differential equation with a homoclinic trajectory is ‘chaotic’.

Spectral bequest

The exhibition held 15 paintings and covered over a year of work investigating the relationship of tonal interactions in a large body of work. This modulates suite of paintings comprised many enigmatic, mystical images, beautifully painted in a classical style. This is a solo exhibition of a series of metaphysical paintings, exhibited for the first time at a leading gallery in Brisbane.

Novel spectral descriptor for object shape

In this paper, we propose a novel descriptor for shapes. The proposed descriptor is obtained from 3D spherical harmonics. The inadequacy of 2D spherical harmonics is addressed and the method to obtain 3D spherical harmonics is described. 3D spherical harmonics requires construction of a 3D model which implicitly represents rich features of objects. Spherical harmonics are used to obtain descriptors from the 3D models. The performance of the proposed method is compared against the CSS approach which is the MPEG-7 descriptor for shape contour. MPEG-7 dataset of shape contours, namely, CE-1 is used to perform the experiments. It is shown that the proposed method is effective.

Spectral shape descriptor using spherical harmonics

In this paper, we propose a spectral descriptor for shapes of objects. The method relies on transforming the 2D objects into 3D space; distance transform and scale space theory is used to transform objects into 3D space. Spherical harmonics of the voxel grid are used to obtain shape descriptors. The proposed methods are compared against two existing methods which use spherical harmonics for shape based retrieval of images. Comparison is done based on ranking of images which is articulated in recall-precision curves. MPEG-7 Still Images Content Set is used for performing experiments. Experimental results show that the performance of the proposed descriptor is significantly better than other methods in the same category.

Guided wave propagation and spectral element method for debonding damage assessment in RC structures

A concrete–steel interface spectral element is developed to study the guided wave propagation along the steel rebar in the concrete. Scalar damage parameters characterizing changes in the interface (debonding damage) are incorporated into the formulation of the spectral finite element that is used for damage detection of reinforced concrete structures. Experimental tests are carried out on a reinforced concrete beam with embedded piezoelectric elements to verify the performance of the proposed model and algorithm. Parametric studies are performed to evaluate the effect of different damage scenarios on wave propagation in the reinforced concrete structures. Numerical simulations and experimental results show that the method is effective to model wave propagation along the steel rebar in concrete and promising to detect damage in the concrete–steel interface.