Scene invariant crowd counting and crowd occupancy analysis

In public places, crowd size may be an indicator of congestion, delay, instability, or of abnormal events, such as a fight, riot or emergency. Crowd related information can also provide important business intelligence such as the distribution of people throughout spaces, throughput rates, and local densities. A major drawback of many crowd counting approaches is their reliance on large numbers of holistic features, training data requirements of hundreds or thousands of frames per camera, and that each camera must be trained separately. This makes deployment in large multi-camera environments such as shopping centres very costly and difficult. In this chapter, we present a novel scene-invariant crowd counting algorithm that uses local features to monitor crowd size. The use of local features allows the proposed algorithm to calculate local occupancy statistics, scale to conditions which are unseen in the training data, and be trained on significantly less data. Scene invariance is achieved through the use of camera calibration, allowing the system to be trained on one or more viewpoints and then deployed on any number of new cameras for testing without further training. A pre-trained system could then be used as a ‘turn-key’ solution for crowd counting across a wide range of environments, eliminating many of the costly barriers to deployment which currently exist.

Non-invasive, quantitative analysis of drug mixtures in containers using spatially offset Raman spectroscopy (SORS) and multivariate statistical analysis

In this paper, spatially offset Raman spectroscopy (SORS) is demonstrated for non-invasively investigating the composition of drug mixtures inside an opaque plastic container. The mixtures consisted of three components including a target drug (acetaminophen or phenylephrine hydrochloride) and two diluents (glucose and caffeine). The target drug concentrations ranged from 5% to 100%. After conducting SORS analysis to ascertain the Raman spectra of the concealed mixtures, principal component analysis (PCA) was performed on the SORS spectra to reveal trends within the data. Partial least squares (PLS) regression was used to construct models that predicted the concentration of each target drug, in the presence of the other two diluents. The PLS models were able to predict the concentration of acetaminophen in the validation samples with a root-mean-square error of prediction (RMSEP) of 3.8% and the concentration of phenylephrine hydrochloride with an RMSEP of 4.6%. This work demonstrates the potential of SORS, used in conjunction with multivariate statistical techniques, to perform non-invasive, quantitative analysis on mixtures inside opaque containers. This has applications for pharmaceutical analysis, such as monitoring the degradation of pharmaceutical products on the shelf, in forensic investigations of counterfeit drugs, and for the analysis of illicit drug mixtures which may contain multiple components.

From critique to cultural recovery: critical futures studies and casual layered analysis

Critical futures studies is not about the careers of a few scholars, rather it is about projects that transcend the narrow boundaries of the self. This biographical monograph examines the life and work of Richard Slaughter and Sohail Inayatullah.

Three-dimensional geological modelling and multivariate statistical analysis of water chemistry data to analyse and visualise aquifer structure and groundwater composition in the Wairau Plain, Marlborough District, New Zealand

Concerns regarding groundwater contamination with nitrate and the long-term sustainability of groundwater resources have prompted the development of a multi-layered three dimensional (3D) geological model to characterise the aquifer geometry of the Wairau Plain, Marlborough District, New Zealand. The 3D geological model which consists of eight litho-stratigraphic units has been subsequently used to synthesise hydrogeological and hydrogeochemical data for different aquifers in an approach that aims to demonstrate how integration of water chemistry data within the physical framework of a 3D geological model can help to better understand and conceptualise groundwater systems in complex geological settings. Multivariate statistical techniques(e.g. Principal Component Analysis and Hierarchical Cluster Analysis) were applied to groundwater chemistry data to identify hydrochemical facies which are characteristic of distinct evolutionary pathways and a common hydrologic history of groundwaters. Principal Component Analysis on hydrochemical data demonstrated that natural water-rock interactions, redox potential and human agricultural impact are the key controls of groundwater quality in the Wairau Plain. Hierarchical Cluster Analysis revealed distinct hydrochemical water quality groups in the Wairau Plain groundwater system. Visualisation of the results of the multivariate statistical analyses and distribution of groundwater nitrate concentrations in the context of aquifer lithology highlighted the link between groundwater chemistry and the lithology of host aquifers. The methodology followed in this study can be applied in a variety of hydrogeological settings to synthesise geological, hydrogeological and hydrochemical data and present them in a format readily understood by a wide range of stakeholders. This enables a more efficient communication of the results of scientific studies to the wider community.

A comparative study of the number and mass of fine particles emitted with diesel fuel and marine gas oil (MGO)

The current investigation reports on diesel particulate matter emissions, with special interest in fine particles from the combustion of two base fuels. The base fuels selected were diesel fuel and marine gas oil (MGO). The experiments were conducted with a four-stroke, six-cylinder, direct injection diesel engine. The results showed that the fine particle number emissions measured by both SMPS and ELPI were higher with MGO compared to diesel fuel. It was observed that the fine particle number emissions with the two base fuels were quantitatively different but qualitatively similar. The gravimetric (mass basis) measurement also showed higher total particulate matter (TPM) emissions with the MGO. The smoke emissions, which were part of TPM, were also higher for the MGO. No significant changes in the mass flow rate of fuel and the brake-specific fuel consumption (BSFC) were observed between the two base fuels.

Microcosm study of ion mobilization and greenhouse gas evolution in soils of a plantation-forested subtropical coastal catchment

This study examined the potential for Fe mobilization and greenhouse gas (GHG, e.g. CO2, and CH4) evolution in SEQ soils associated with a range of plantation forestry practices and water-logged conditions. Intact, 30-cm-deep soil cores collected from representative sites were saturated and incubated for 35 days in the laboratory, with leachate and headspace gas samples periodically collected. Minimal Fe dissolution was observed in well-drained sand soils associated with mature, first-rotation Pinus and organic Fe complexation, whereas progressive Fe dissolution occurred over 14 days in clear-felled and replanted Pinus soils with low organic matter and non-crystalline Fe fractions. Both CO2 and CH4 effluxes were relatively lower in clear-felled and replanted soils compared with mature, first-rotation Pinus soils, despite the lack of statistically significant variations in total GHG effluxes associated with different forestry practices. Fe dissolution and GHG evolution in low-lying, water-logged soils adjacent to riparian and estuarine, native-vegetation buffer zones were impacted by mineral and physical soil properties. Highest levels of dissolved Fe and GHG effluxes resulted from saturation of riparian loam soils with high Fe and clay content, as well as abundant organic material and Fe-metabolizing bacteria. Results indicate Pinus forestry practices such as clear-felling and replanting may elevate Fe mobilization while decreasing CO2 and CH4 emissions from well-drained, SEQ plantation soils upon heavy flooding. Prolonged water-logging accelerates bacterially mediated Fe cycling in low-lying, clay-rich soils, leading to substantial Fe dissolution, organic matter mineralization, and CH4 production in riparian native-vegetation buffer zones.

Association between prostinogen (KLK15) genetic variants and prostate cancer risk and aggressiveness in Australia and a meta-analysis of GWAS data

Background: Kallikrein 15 (KLK15)/Prostinogen is a plausible candidate for prostate cancer susceptibility. Elevated KLK15 expression has been reported in prostate cancer and it has been described as an unfavorable prognostic marker for the disease. Objectives: We performed a comprehensive analysis of association of variants in the KLK15 gene with prostate cancer risk and aggressiveness by genotyping tagSNPs, as well as putative functional SNPs identified by extensive bioinformatics analysis. Methods and Data Sources: Twelve out of 22 SNPs, selected on the basis of linkage disequilibrium pattern, were analyzed in an Australian sample of 1,011 histologically verified prostate cancer cases and 1,405 ethnically matched controls. Replication was sought from two existing genome wide association studies (GWAS): the Cancer Genetic Markers of Susceptibility (CGEMS) project and a UK GWAS study. Results: Two KLK15 SNPs, rs2659053 and rs3745522, showed evidence of association (p, 0.05) but were not present on the GWAS platforms. KLK15 SNP rs2659056 was found to be associated with prostate cancer aggressiveness and showed evidence of association in a replication cohort of 5,051 patients from the UK, Australia, and the CGEMS dataset of US samples. A highly significant association with Gleason score was observed when the data was combined from these three studies with an Odds Ratio (OR) of 0.85 (95% CI = 0.77-0.93; p = 2.7610 24). The rs2659056 SNP is predicted to alter binding of the RORalpha transcription factor, which has a role in the control of cell growth and differentiation and has been suggested to control the metastatic behavior of prostate cancer cells. Conclusions: Our findings suggest a role for KLK15 genetic variation in the etiology of prostate cancer among men of European ancestry, although further studies in very large sample sets are necessary to confirm effect sizes.

CT and X-Ray analysis of sagittal curve changes following thoracoscopic anterior scoliosis surgery

Normal thoracic kyphosis Cobb angle for T5-T12 is most commonly reported as a range of 20-40º [1]. Patients with adolescent idiopathic scoliosis (AIS) exhibit a reduced thoracic kyphosis or hypokyphosis [2] accompanying the coronal and rotary distortion components. As a result, surgical restoration of the thoracic kyphosis while maintaining lumbar lordosis and overall sagittal balance is a critical aspect of achieving good clinical outcomes in AIS patients. Previous studies report an increase in thoracic kyphosis after anterior surgical approaches [3] and a flattening of sagittal contours following posterior approaches [4]. Difficulties with measuring sagittal parameters on radiographs are avoided with reformatted sagittal CT reconstructions due to the superior endplate clarity afforded by this imaging modality and are the subject of analysis in this study.

‘Hot chicks’, ‘better parties’ or academic stuff : perceptions of a regional university campus using Repertory Grid Analysis and Importance-performance Analysis

In the increasingly competitive Australian tertiary education market, a consumer orientation is essential. This is particularly so for small regional campuses competing with larger universities in the state capitals. Campus management need to carefully monitor both the perceptions of prospective students within the catchment area, and the (dis)satisfaction levels of current students. This study reports the results of an exploratory investigation into the perceptions held of a regional campus, using two techniques that have arguably been underutilised in the education marketing literature. Repertory Grid Analysis, a technique developed almost fifty years ago, was used to identify attributes deemed salient to year 12 high school students at the time they were applying for university places. Importance-performance analysis (IPA), developed three decades ago, was then used to identify attributes that were determinant for a new cohort of first year undergraduate students. The paper concludes that group applications of Repertory Grid offer education market researchers a useful means for identifying attributes used by high school students to differentiate universities, and that IPA is a useful technique for guiding promotional decision making. In this case, the two techniques provided a quick, economical and effective snapshot of market perceptions, which can be used as a foundation for the development of an ongoing market research programme.

Experimental impact and finite element analysis of a composite, portable road safety barrier

This thesis provides an experimental and computational platform for investigating the performance and behaviour of water filled, plastic portable road safety barriers in an isolated impact scenario. A schedule of experimental impact tests were conducted assessing the impact response of an existing design of road safety barrier utilising a novel horizontal impact testing system. A coupled finite element and smooth particle hydrodynamic model of the barrier system was developed and validated against the results of the experimental tests. The validated model was subsequently used to assess the effect of certain composite materials on the impact performance of the water filled, portable road safety barrier system.