Development of descriptor tools for the characterization of Australian sugar mill evaporator scale

Cleaning of sugar mill evaporators is an expensive exercise. Identifying the scale components assists in determining which chemical cleaning agents would result in effective evaporator cleaning. The current methods (based on x-ray diffraction techniques, ion exchange/high performance liquid chromatography and thermogravimetry/differential thermal analysis) used for scale characterisation are difficult, time consuming and expensive, and cannot be performed in a conventional analytical laboratory or by mill staff. The present study has examined the use of simple descriptor tests for the characterisation of Australian sugar mill evaporator scales. Scale samples were obtained from seven Australian sugar mill evaporators by mechanical means. The appearance, texture and colour of the scale were noted before the samples were characterised using x-ray fluorescence and x-ray powder diffraction to determine the compounds present. A number of commercial analytical test kits were used to determine the phosphate and calcium contents of scale samples. Dissolution experiments were carried out on the scale samples with selected cleaning agents to provide relevant information about the effect the cleaning agents have on different evaporator scales. Results have shown that by simply identifying the colour and the appearance of the scale, the elemental composition and knowing from which effect the scale originates, a prediction of the scale composition can be made. These descriptors and dissolution experiments on scale samples can be used to provide factory staff with an on-site rapid process to predict the most effective chemicals for chemical cleaning of the evaporators.

A biologically inspired object spectral-texture descriptor and its application to vegetation classification in power-line corridors

The use of appropriate features to represent an output class or object is critical for all classification problems. In this paper, we propose a biologically inspired object descriptor to represent the spectral-texture patterns of image-objects. The proposed feature descriptor is generated from the pulse spectral frequencies (PSF) of a pulse coupled neural network (PCNN), which is invariant to rotation, translation and small scale changes. The proposed method is first evaluated in a rotation and scale invariant texture classification using USC-SIPI texture database. It is further evaluated in an application of vegetation species classification in power line corridor monitoring using airborne multi-spectral aerial imagery. The results from the two experiments demonstrate that the PSF feature is effective to represent spectral-texture patterns of objects and it shows better results than classic color histogram and texture features.

Development of descriptor tools for the characterisation of Australian sugar mill evaporator scale

Cleaning of sugar mill evaporators is an expensive exercise. Identifying the scale components assists in determining which chemical cleaning agents would result in effective evaporator cleaning. The current methods (based on x-ray diffraction techniques, ion exchange/high performance liquid chromatography and thermogravimetry/differential thermal analysis) used for scale characterisation are difficult, time consuming and expensive, and cannot be performed in a conventional analytical laboratory or by mill staff. The present study has examined the use of simple descriptor tests for the characterisation of Australian sugar mill evaporator scales. Scale samples were obtained from seven Australian sugar mill evaporators by mechanical means. The appearance, texture and colour of the scale were noted before the samples were characterised using x-ray fluorescence and x-ray powder diffraction to determine the compounds present. A number of commercial analytical test kits were used to determine the phosphate and calcium contents of scale samples. Dissolution experiments were carried out on the scale samples with selected cleaning agents to provide relevant information about the effect the cleaning agents have on different evaporator scales. Results have shown that by simply identifying the colour and the appearance of the scale, the elemental composition and knowing from which effect the scale originates, a prediction of the scale composition can be made. These descriptors and dissolution experiments on scale samples can be used to provide factory staff with an on-site rapid process to predict the most effective chemicals for chemical cleaning of the evaporators.

A method to quantify a descriptor's illumination variance

This paper presents a new metric, which we call the lighting variance ratio, for quantifying descriptors in terms of their variance to illumination changes. In many applications it is desirable to have descriptors that are robust to changes in illumination, especially in outdoor environments. The lighting variance ratio is useful for comparing descriptors and determining if a descriptor is lighting invariant enough for a given environment. The metric is analysed across a number of datasets, cameras and descriptors. The results show that the upright SIFT descriptor is typically the most lighting invariant descriptor.

Understanding how to enhance business creativity

This PhD study examines some of what happens in an individual’s mind regarding creativity during problem solving within an organisational context. It presents innovations related to creative motivation, cognitive style and framing effects that can be applied by managers to enhance individual employee creativity within the organisation and thereby assist organisations to become more innovative. The project delivers an understanding of how to leverage natural changes in creative motivation levels during problem solving. This pattern of response is called Creative Resolve Response (CRR). The project also presents evidence of how framing effects can be used to influence decisions involving creative options in order to enhance the potential for managers get employees to select creative options more often for implementation. The study’s objectives are to understand: • How creative motivation changes during problem solving • How cognitive style moderates these creative motivation changes • How framing effects apply to decisions involving creative options to solve problems • How cognitive style moderate these framing effects The thesis presents the findings from three controlled experiments based around self reports during contrived problem solving and decision making situations. The first experiment suggests that creative motivation varies in a predictable and systematic way during problem solving as a function of the problem solver’s perception of progress. The second experiment suggests that there are specific framing effects related to decisions involving creativity. It seems that simply describing an alternative as innovative may activate perceptual biases that overcome risk based framing effects. The third experiment suggests that cognitive style moderates decisions involving creativity in complex ways. It seems that in some contexts, decision makers will prefer a creative option, regardless of their cognitive style, if this option is both outside the bounds of what is officially allowed and yet ultimately safe. The thesis delivers innovation on three levels: theoretical, methodological and empirical. The highlights of these findings are outlined below: 1. Theoretical innovation with the conceptualisation of Creative Resolve Response based on an extension of Amabile’s research regarding creative motivation. 2. Theoretical innovation linking creative motivation and Kirton’s research on cognitive style. 3. Theoretical innovation linking both risk based and attribute framing effects to cognitive style. 4. Methodological innovation for defining and testing preferences for creative solution implementation in the form of operationalised creativity decision alternatives. 5. Methodological innovation to identify extreme decision options by applying Shafir’s findings regarding attribute framing effects in reverse to create a test. 6. Empirical innovation with statistically significant research findings which indicate creative motivation varies in a systematic way. 7. Empirical innovation with statistically significant research findings which identify innovation descriptor framing effects 8. Empirical innovation with statistically significant research findings which expand understanding of Kirton’s cognitive style descriptors including the importance of safe rule breaking. 9. Empirical innovation with statistically significant research findings which validate how framing effects do apply to decisions involving operationalised creativity. Drawing on previous research related to creative motivation, cognitive style, framing effects and supervisor interactions with employees, this study delivers insights which can assist managers to increase the production and implementation of creativity in organisations. Hopefully this will result in organisations which are more innovative. Such organisations have the potential to provide ongoing economic and social benefits.

Letting go of Neo-Liberalism (with some help from Michel Foucault)

Neo-liberalism has become one of the boom concepts of our time. From its original reference point as a descriptor of the economics of the “Chicago School” such as Milton Friedman, or authors such as Friedrich von Hayek, neo-liberalism has become an all-purpose descriptor and explanatory device for phenomena as diverse as Bollywood weddings, standardized testing in schools, violence in Australian cinema, and the digitization of content in public libraries. Moreover, it has become an entirely pejorative term: no-one refers to their own views as “neo-liberal”, but it rather refers to the erroneous views held by others, whether they acknowledge this or not. Neo-liberalism as it has come to be used, then, bears many of the hallmarks of a dominant ideology theory in the classical Marxist sense, even if it is often not explored in these terms. This presentation will take the opportunity provided by the English language publication of Michel Foucault’s 1978-79 lectures, under the title of The Birth of Biopolitics, to consider how he used the term neo-liberalism, and how this equates with its current uses in critical social and cultural theory. It will be argued that Foucault did not understand neo-liberalism as a dominant ideology in these lectures, but rather as marking a point of inflection in the historical evolution of liberal political philosophies of government. It will also be argued that his interpretation of neo-liberalism was more nuanced and more comparative than the more recent uses of Foucault in the literature on neo-liberalism. It will also look at how Foucault develops comparative historical models of liberal capitalism in The Birth of Biopolitics, arguing that this dimension of his work has been lost in more recent interpretations, which tend to retro-fit Foucault to contemporary critiques of either U.S. neo-conservatism or the “Third Way” of Tony Blair’s New Labour in the UK.

Color and texture feature fusion using kernel PCA with application to object-based vegetation species classification

A good object representation or object descriptor is one of the key issues in object based image analysis. To effectively fuse color and texture as a unified descriptor at object level, this paper presents a novel method for feature fusion. Color histogram and the uniform local binary patterns are extracted from arbitrary-shaped image-objects, and kernel principal component analysis (kernel PCA) is employed to find nonlinear relationships of the extracted color and texture features. The maximum likelihood approach is used to estimate the intrinsic dimensionality, which is then used as a criterion for automatic selection of optimal feature set from the fused feature. The proposed method is evaluated using SVM as the benchmark classifier and is applied to object-based vegetation species classification using high spatial resolution aerial imagery. Experimental results demonstrate that great improvement can be achieved by using proposed feature fusion method.

Michel Foucault's 'the birth of biopolitics' and contemporary neo-liberalism debates

Neo-liberalism has become one of the boom concepts of our time. From its original reference point as a descriptor of the economics of the ‘Chicago School’ or authors such as Friedrich von Hayek, neo-liberalism has become an all-purpose concept, explanatory device and basis for social critique. This presentation evaluates Michel Foucault’s 1978–79 lectures, published as The Birth of Biopolitics, to consider how he used the term neo-liberalism, and how this equates with its current uses in critical social and cultural theory. It will be argued that Foucault did not understand neo-liberalism as a dominant ideology in these lectures, but rather as marking a point of inflection in the historical evolution of liberal political philosophies of government. It will also be argued that his interpretation of neo-liberalism was more nuanced and more comparative than more recent contributions. The article points towards an attempt to theorize comparative historical models of liberal capitalism.

Re-framing fashion : from original and copy to adaptation

This article discusses the interaction between original and adaptation in the fashion system; the study also analyses, at a micro level, practices of adaptation adopted by consumers when making and re-making fashionable clothes. The article shows that the distinction between original and copy is historically determined as it grew out of the romantic notion of the authentic work of art. This article suggests that, in the impossibility to determine copyright in fashion, adaptation is a better descriptor of practices that transform garments; the concept of adaptation also abolishes trite notions of fashion as pastiche or bricolage, arguing for as a way to look at the many variations and re-contextualisations of garments historically and cross-culturally.

Spectral–texture feature extraction using statistical moments with application to object-based vegetation species classification

The use of appropriate features to characterise an output class or object is critical for all classification problems. In order to find optimal feature descriptors for vegetation species classification in a power line corridor monitoring application, this article evaluates the capability of several spectral and texture features. A new idea of spectral–texture feature descriptor is proposed by incorporating spectral vegetation indices in statistical moment features. The proposed method is evaluated against several classic texture feature descriptors. Object-based classification method is used and a support vector machine is employed as the benchmark classifier. Individual tree crowns are first detected and segmented from aerial images and different feature vectors are extracted to represent each tree crown. The experimental results showed that the proposed spectral moment features outperform or can at least compare with the state-of-the-art texture descriptors in terms of classification accuracy. A comprehensive quantitative evaluation using receiver operating characteristic space analysis further demonstrates the strength of the proposed feature descriptors.

Unusual Event Detection in Crowded Scenes Using Bag of LBPs in spatio-temporal patches

Modelling events in densely crowded environments remains challenging, due to the diversity of events and the noise in the scene. We propose a novel approach for anomalous event detection in crowded scenes using dynamic textures described by the Local Binary Patterns from Three Orthogonal Planes (LBP-TOP) descriptor. The scene is divided into spatio-temporal patches where LBP-TOP based dynamic textures are extracted. We apply hierarchical Bayesian models to detect the patches containing unusual events. Our method is an unsupervised approach, and it does not rely on object tracking or background subtraction. We show that our approach outperforms existing state of the art algorithms for anomalous event detection in UCSD dataset.

Negative determinant of Hessian features

Local image feature extractors that select local maxima of the determinant of Hessian function have been shown to perform well and are widely used. This paper introduces the negative local minima of the determinant of Hessian function for local feature extraction. The properties and scale-space behaviour of these features are examined and found to be desirable for feature extraction. It is shown how this new feature type can be implemented along with the existing local maxima approach at negligible extra processing cost. Applications to affine covariant feature extraction and sub-pixel precise corner extraction are demonstrated. Experimental results indicate that the new corner detector is more robust to image blur and noise than existing methods. It is also accurate for a broader range of corner geometries. An affine covariant feature extractor is implemented by combining the minima of the determinant of Hessian with existing scale and shape adaptation methods. This extractor can be implemented along side the existing Hessian maxima extractor simply by finding both minima and maxima during the initial extraction stage. The minima features increase the number of correspondences by two to four fold. The additional minima features are very distinct from the maxima features in descriptor space and do not make the matching process more ambiguous.

Class contestations and Australia’s resource boom : the emergence of the ‘cashed-up bogan’

This article examines the figure of the ‘Cashed-up Bogan’ or ‘Cub’ in Australian media from 2006 to 2009. It explains that ‘Bogan’, like that of ‘Chav’ in Britain, is a widely engaged negative descriptor for the white working-class poor. In contrast, ‘Cubs’ have economic capital. This capital, and the Cub’s emergence, is linked to Australia’s resource boom of recent decades when the need for skilled labour allowed for a highly demarcated segment of the working class to earn relatively high incomes in the mining sector and to participate in consumption. We argue that access to economic capital has provided the Cub with mobility to enter the everyday spaces of the middle class, but this has caused disruption and anxiety to middle-class hegemony. As a result, the middle class has redrawn and reinforced class-infused symbolic and cultural boundaries, whereby, despite their wealth, pernicious media representations mark Cubs as ‘other’ to the middle-class deservingness, taste and morality.