A literature review on research methodologies of gross pollutant traps

This paper presents a comprehensive review of scientific and grey literature on gross pollutant traps (GPTs). GPTs are designed with internal screens to capture gross pollutants—organic matter and anthropogenic litter. Their application involves professional societies, research organisations, local city councils, government agencies and the stormwater industry—often in partnership. In view of this, the 113 references include unpublished manuscripts from these bodies along with scientific peer-reviewed conference papers and journal articles. The literature reviewed was organised into a matrix of six main devices and nine research areas (testing methodologies) which include: design appraisal study, field monitoring/testing, experimental flow fields, gross pollutant capture/retention characteristics, residence time calculations, hydraulic head loss, screen blockages, flow visualisations and computational fluid dynamics (CFD). When the fifty-four item matrix was analysed, twenty-eight research gaps were found in the tabulated literature. It was also found that the number of research gaps increased if only the scientific literature was considered. It is hoped, that in addition to informing the research community at QUT, this literature review will also be of use to other researchers in this field.

Researching the 'reception' of indigenous affairs in Australia

The Reporting and Reception of Indigenous Issues in the Australian Media was a three year project financed by the Australian government through its Australian Research Council Large Grants Scheme and run by Professor John Hartley (of Murdoch and then Edith Cowan University, Western Australia). The purpose of the research was to map the ways in which indigeneity was constructed and circulated in Australia's mediasphere. The analysis of the 'reporting' element of the project was almost straightforward: a mixture of content analysis of a large number of items in the media, and detailed textual analysis of a smaller number of key texts. The discoveries were interesting - that when analysis approaches the media as a whole, rather than focussing exclusively on news or serious drama genres, then representation of indigeneity is not nearly as homogenous as has previously been assumed. And if researchers do not explicitly set out to uncover racism in every text, it is by no means guaranteed they will find it1. The question of how to approach the 'reception' of these issues - and particularly reception by indigenous Australians - proved to be a far more challenging one. In attempting to research this area, Hartley and I (working as a research assistant on the project) often found ourselves hampered by the axioms that underlie much media research. Traditionally, the 'reception' of media by indigenous people in Australia has been researched in ethnographic ways. This research repeatedly discovers that indigenous people in Australia are powerless in the face of new forms of media. Indigenous populations are represented as victims of aggressive and powerful intrusions: ‘What happens when a remote community is suddenly inundated by broadcast TV?’; ‘Overnight they will go from having no radio and television to being bombarded by three TV channels’; ‘The influence of film in an isolated, traditionally oriented Aboriginal community’2. This language of ‘influence’, ‘bombarded’, and ‘inundated’, presents metaphors not just of war but of a war being lost. It tells of an unequal struggle, of a more powerful force impinging upon a weaker one. What else could be the relationship of an Aboriginal audience to something which is ‘bombarding’ them? Or by which they are ‘inundated’? This attitude might best be summed up by the title of an article by Elihu Katz: ‘Can authentic cultures survive new media?’3. In such writing, there is little sense that what is being addressed might be seen as a series of discursive encounters, negotiations and acts of meaning-making in which indigenous people — communities and audiences —might be productive. Certainly, the points of concern in this type of writing are important. The question of what happens when a new communication medium is summarily introduced to a culture is certainly an important one. But the language used to describe this interaction is a misleading one. And it is noticeable that such writing is fascinated with the relationship of only traditionally-oriented Aboriginal communities to the media of mass communication.

Thermal stability of the ‘cave’ mineral brushite CaHPO4•2H2O -mechanism of formation and decomposition

Thermogravimetry combined with evolved gas mass spectrometry has been used to ascertain the stability of the ‘cave’ mineral brushite. X-ray diffraction shows that brushite from the Jenolan Caves is very pure. Thermogravimetric analysis coupled with ion current mass spectrometry shows a mass loss at 111°C due to loss of water of hydration. A further decomposition step occurs at 190°C with the conversion of hydrogen phosphate to a mixture of calcium ortho-phosphate and calcium pyrophosphate. TG-DTG shows the mineral is not stable above 111°C. A mechanism for the formation of brushite on calcite surfaces is proposed, and this mechanism has relevance to the formation of brushite in urinary tracts.

Influence of biochars on flux of N2O and CO2 from Ferrosol

Biochars produced by slow pyrolysis of greenwaste (GW), poultry litter (PL), papermill waste (PS), and biosolids (BS) were shown to reduce N₂O emissions from an acidic Ferrosol. Similar reductions were observed for the untreated GW feedstock. Soil was amended with biochar or feedstock giving application rates of 1 and 5%. Following an initial incubation, nitrogen (N) was added at 165 kg/ha as urea. Microcosms were again incubated before being brought to 100% water-filled porosity and held at this water content for a further 47 days. The flooding phase accounted for the majority (<80%) of total N₂O emissions. The control soil released 3165 mg N₂O-N/m², or 15.1% of the available N as N₂O. Amendment with 1 and 5% GW feedstock significantly reduced emissions to 1470 and 636 mg N₂O-N/m², respectively. This was equivalent to 8.6 and 3.8% of applied N. The GW biochar produced at 350°C was least effective in reducing emissions, resulting in 1625 and 1705 mg N₂O-N/m² for 1 and 5% amendments. Amendment with BS biochar at 5% had the greatest impact, reducing emissions to 518 mg N₂O-N/m², or 2.2% of the applied N over the incubation period. Metabolic activity as measured by CO₂ production could not explain the differences in N₂O emissions between controls and amendments, nor could NH₄⁺ or NO₃^– concentrations in biochar-amended soils. A decrease in NH₄⁺ and NO₃^– following GW feedstock application is likely to have been responsible for reducing N₂O emissions from this amendment. Reduction in N₂O emissions from the biochar-amended soils was attributed to increased adsorption of NO₃^–. Small reductions are possible due to improved aeration and porosity leading to lower levels of denitrification and N₂O emissions. Alternatively, increased pH was observed, which can drive denitrification through to dinitrogen during soil flooding.

Relative entropy rate based design for linear hybrid system models

Hybrid system representations have been applied to many challenging modeling situations. In these hybrid system representations, a mixture of continuous and discrete states is used to capture the dominating behavioural features of a nonlinear, possible uncertain, model under approximation. Unfortunately, the problem of how to best design a suitable hybrid system model has not yet been fully addressed. This paper proposes a new joint state measurement relative entropy rate based approach for this design purpose. Design examples and simulation studies are presented which highlight the benefits of our proposed design approaches.

Platinum/graphene nanosheet/SiC contacts and their application for hydrogen gas sensing

Pt/graphene nanosheet/SiC based devices are fabricated and characterized and their performances toward hydrogen gas are investigated. The graphene nanosheets are synthesized via the reduction of spray-coated graphite oxide deposited onto SiC substrates. Raman and X-ray photoelectron spectroscopies indicate incomplete reduction of the graphite oxide, resulting in partially oxidized graphene nanosheet layers of less than 10 nm thickness. The effects of interfaces on the nonlinear behavior of the Pt/graphene and graphene/SiC junctions are investigated. Current-voltage measurements of the sensors toward 1% hydrogen in synthetic air gas mixture at various temperatures ranging up to 100. ° C are performed. From the dynamic response, a voltage shift of ∼100 mV is recorded for 1% hydrogen at a constant current bias of 1 mA at 100. °C. © 2010 American Chemical Society.

Application of higher order spectra to identify epileptic EEG

Epilepsy is characterized by the spontaneous and seemingly unforeseeable occurrence of seizures, during which the perception or behavior of patients is disturbed. An automatic system that detects seizure onsets would allow patients or the people near them to take appropriate precautions, and could provide more insight into this phenomenon. Various methods have been proposed to predict the onset of seizures based on EEG recordings. The use of nonlinear features motivated by the higher order spectra (HOS) has been reported to be a promising approach to differentiate between normal, background (pre-ictal) and epileptic EEG signals. In this work, we made a comparative study of the performance of Gaussian mixture model (GMM) and Support Vector Machine (SVM) classifiers using the features derived from HOS and from the power spectrum. Results show that the selected HOS based features achieve 93.11% classification accuracy compared to 88.78% with features derived from the power spectrum for a GMM classifier. The SVM classifier achieves an improvement from 86.89% with features based on the power spectrum to 92.56% with features based on the bispectrum.

Vector quantization based Gaussian modeling for speaker verification

Gaussian mixture models (GMMs) have become an established means of modeling feature distributions in speaker recognition systems. It is useful for experimentation and practical implementation purposes to develop and test these models in an efficient manner particularly when computational resources are limited. A method of combining vector quantization (VQ) with single multi-dimensional Gaussians is proposed to rapidly generate a robust model approximation to the Gaussian mixture model. A fast method of testing these systems is also proposed and implemented. Results on the NIST 1996 Speaker Recognition Database suggest comparable and in some cases an improved verification performance to the traditional GMM based analysis scheme. In addition, previous research for the task of speaker identification indicated a similar system perfomance between the VQ Gaussian based technique and GMMs

An approach to statistical lip modelling for speaker identification via chromatic feature extraction

This paper presents a novel technique for the tracking of moving lips for the purpose of speaker identification. In our system, a model of the lip contour is formed directly from chromatic information in the lip region. Iterative refinement of contour point estimates is not required. Colour features are extracted from the lips via concatenated profiles taken around the lip contour. Reduction of order in lip features is obtained via principal component analysis (PCA) followed by linear discriminant analysis (LDA). Statistical speaker models are built from the lip features based on the Gaussian mixture model (GMM). Identification experiments performed on the M2VTS¹ database, show encouraging results

New variational Bayesian approaches for statistical data mining : with applications to profiling and differentiating habitual consumption behaviour of customers in the wireless telecommunication industry

This thesis investigates profiling and differentiating customers through the use of statistical data mining techniques. The business application of our work centres on examining individuals’ seldomly studied yet critical consumption behaviour over an extensive time period within the context of the wireless telecommunication industry; consumption behaviour (as oppose to purchasing behaviour) is behaviour that has been performed so frequently that it become habitual and involves minimal intentions or decision making. Key variables investigated are the activity initialised timestamp and cell tower location as well as the activity type and usage quantity (e.g., voice call with duration in seconds); and the research focuses are on customers’ spatial and temporal usage behaviour. The main methodological emphasis is on the development of clustering models based on Gaussian mixture models (GMMs) which are fitted with the use of the recently developed variational Bayesian (VB) method. VB is an efficient deterministic alternative to the popular but computationally demandingMarkov chainMonte Carlo (MCMC) methods. The standard VBGMMalgorithm is extended by allowing component splitting such that it is robust to initial parameter choices and can automatically and efficiently determine the number of components. The new algorithm we propose allows more effective modelling of individuals’ highly heterogeneous and spiky spatial usage behaviour, or more generally human mobility patterns; the term spiky describes data patterns with large areas of low probability mixed with small areas of high probability. Customers are then characterised and segmented based on the fitted GMM which corresponds to how each of them uses the products/services spatially in their daily lives; this is essentially their likely lifestyle and occupational traits. Other significant research contributions include fitting GMMs using VB to circular data i.e., the temporal usage behaviour, and developing clustering algorithms suitable for high dimensional data based on the use of VB-GMM.

Cross likelihood ratio based speaker clustering using eigenvoice models

This paper proposes the use of eigenvoice modeling techniques with the Cross Likelihood Ratio (CLR) as a criterion for speaker clustering within a speaker diarization system. The CLR has previously been shown to be a robust decision criterion for speaker clustering using Gaussian Mixture Models. Recently, eigenvoice modeling techniques have become increasingly popular, due to its ability to adequately represent a speaker based on sparse training data, as well as an improved capture of differences in speaker characteristics. This paper hence proposes that it would be beneficial to capitalize on the advantages of eigenvoice modeling in a CLR framework. Results obtained on the 2002 Rich Transcription (RT-02) Evaluation dataset show an improved clustering performance, resulting in a 35.1% relative improvement in the overall Diarization Error Rate (DER) compared to the baseline system.

Visual voice activity detection using frontal versus profile views

Visual activity detection of lip movements can be used to overcome the poor performance of voice activity detection based solely in the audio domain, particularly in noisy acoustic conditions. However, most of the research conducted in visual voice activity detection (VVAD) has neglected addressing variabilities in the visual domain such as viewpoint variation. In this paper we investigate the effectiveness of the visual information from the speaker’s frontal and profile views (i.e left and right side views) for the task of VVAD. As far as we are aware, our work constitutes the first real attempt to study this problem. We describe our visual front end approach and the Gaussian mixture model (GMM) based VVAD framework, and report the experimental results using the freely available CUAVE database. The experimental results show that VVAD is indeed possible from profile views and we give a quantitative comparison of VVAD based on frontal and profile views The results presented are useful in the development of multi-modal Human Machine Interaction (HMI) using a single camera, where the speaker’s face may not always be frontal.