Large scale participatory acoustic sensor data analysis : tools and reputation models to enhance effectiveness

Acoustic sensors play an important role in augmenting the traditional biodiversity monitoring activities carried out by ecologists and conservation biologists. With this ability however comes the burden of analysing large volumes of complex acoustic data. Given the complexity of acoustic sensor data, fully automated analysis for a wide range of species is still a significant challenge. This research investigates the use of citizen scientists to analyse large volumes of environmental acoustic data in order to identify bird species. Specifically, it investigates ways in which the efficiency of a user can be improved through the use of species identification tools and the use of reputation models to predict the accuracy of users with unidentified skill levels. Initial experimental results are reported.

Leveraging Web 2.0 data for scalable semi-supervised learning of domain-specific sentiment lexicons

Since manually constructing domain-specific sentiment lexicons is extremely time consuming and it may not even be feasible for domains where linguistic expertise is not available. Research on the automatic construction of domain-specific sentiment lexicons has become a hot topic in recent years. The main contribution of this paper is the illustration of a novel semi-supervised learning method which exploits both term-to-term and document-to-term relations hidden in a corpus for the construction of domain specific sentiment lexicons. More specifically, the proposed two-pass pseudo labeling method combines shallow linguistic parsing and corpusbase statistical learning to make domain-specific sentiment extraction scalable with respect to the sheer volume of opinionated documents archived on the Internet these days. Another novelty of the proposed method is that it can utilize the readily available user-contributed labels of opinionated documents (e.g., the user ratings of product reviews) to bootstrap the performance of sentiment lexicon construction. Our experiments show that the proposed method can generate high quality domain-specific sentiment lexicons as directly assessed by human experts. Moreover, the system generated domain-specific sentiment lexicons can improve polarity prediction tasks at the document level by 2:18% when compared to other well-known baseline methods. Our research opens the door to the development of practical and scalable methods for domain-specific sentiment analysis.

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.

Quality of life and genetics in men with prostate cancer

As family history has been established as a risk factor for prostate cancer, attempts have been made to isolate predisposing genetic variants that are related to hereditary prostate cancer. With many genetic variants still to be identified and investigated, it is not yet possible to fully understand the impact of genetic variants on prostate cancer development. The high survival rates among men with prostate cancer have meant that other issues, such as quality of life (QoL), have also become important. Through their effect on a person’s health, a range of inherited genetic variants may potentially influence QoL in men with prostate cancer, even prior to treatment. Until now, limited research has been conducted on the relationship between genetics and QoL. Thus, this study contributes to an emerging field by aiming to identify certain genetic variants related to the QoL found in men with prostate cancer. It is hoped that this study may lead to future research that will identify men who have an increased risk of a poor QoL following prostate cancer treatment, which will aid in developing treatments that are individually tailored to support them. Previous studies have established that genetic variants of Vascular Endothelial Growth Factor (VEGF) and Insulin-like Growth Factor 1 (IGF-1) may play a role in prostate cancer development. VEGF and IGF-1 have also been reported to be associated with QoL in people with ovarian cancer and colorectal cancer, respectively. This study completed a series of secondary analyses using two major data-sets (from 850 men newly diagnosed with prostate cancer, and approximately 550 men from the general Queensland population), in which genetic variants of VEGF and IGF-1 were investigated for associations with prostate cancer susceptibility and QoL. The first aim of this research was to investigate genetic variants in the VEGF and IGF-I gene for an association with the risk of prostate cancer. It was found that one IGF-1 genetic variant (rs35765) had a statistically significant association with prostate cancer (p = 0.04), and one VEGF genetic variant (rs2146323) had a statistically significant association with advanced prostate cancer (p = 0.02). The estimates suggest that carriers of the CA and AA genotype for rs35765 may have a reduced risk of developing prostate cancer (Odds Ratio (OR) = 0.72, 95% Confidence Interval (CI) = 0.55, 0.95, OR = 0.60, 95% CI = 0.26, 1.39, respectively). Meanwhile, carriers of the CA and AA genotype for rs2146323 may be at increased risk of advanced prostate cancer, which was determined by a Gleason score of above 7 (OR = 1.72, 95% CI = 1.12, 2.63, OR = 1.90, 95% CI = 1.08, 3.34, respectively). Utilising the widely used short-form health survey, the SF-36v2, the second aim of this study was to investigate the relationship between prostate cancer and QoL prior to treatment. Assessing QoL at this time-point was important as little research has been conducted to evaluate if prostate cancer affects QoL regardless of treatment. The analyses found that mean SF-36v2 scale scores related to physical health were higher by at least 0.3 Standard Deviations (SD) among men with prostate cancer than the general population comparison group. This difference was considered clinically significant (defined by group differences in mean SF-36v2 scores by at least 0.3 SD). These differences were also statistically significant (p<0.05). Mean QoL scale scores related to mental health were similar between men with prostate cancer and those from the general population comparison group. The third aim of this study was to investigate genetic variants in the VEGF and IGF-1 gene for an association with QoL in prostate cancer patients prior to their treatment. It was essential to evaluate these relationships prior to treatment, before the involvement of these genes was potentially interrupted by treatment. The analyses found that some genetic variants had a small clinically significant association (0.3 SD) to some QoL domains experienced by these men. However, most relationships were not statistically significant (p>0.05). Most of the associations found identified that a small sub-group of men with prostate cancer (approximately 2%) reported, on average, a slightly better QoL than the majority of the prostate cancer patients. The fourth aim of this research was to investigate whether associations between genetic variants in VEGF and IGF-1 and QoL were specific to men with prostate cancer, or were also applicable to the general male population. It was found that twenty out of one-hundred relationships between the genetic variants of VEGF and IGF-1 and QoL health-measures and scales examined differed between these groups. In the majority of the relationships involving VEGF SNPs that differed, a clinically significant difference (0.3 or more SD) between mean scores among the genotype groups in prostate cancer patients was found, while mean scores among men from the general-population comparison group were similar. For example, prostate cancer participants who carried at least one T allele (CT or TT genotype) for rs3024994 had a clinically significant higher (0.3 SD) mean QoL score in terms of the role-physical scale, than participants who carried the CC genotype. This was not seen among men from the general population sample, as the mean score was similar between genotype groups. The opposite was seen in regards to the IGF-1 SNPs examined. Overall, these relationships were not considered to directly impact on the clinical options for men with prostate cancer. As this study utilised secondary data from two separate studies, there are a number of important limitations that should be acknowledged including issues of multiple comparisons, power, and missing or unavailable data. It is recommended that this study be replicated as a better-designed study that takes greater consideration of the many factors involved in prostate cancer and QoL. Investigation into other genetic variants of VEGF or IGF-1 is also warranted, as is consideration of other genes and their relationship with QoL. Through identifying certain genetic variants that have a modest association to prostate cancer, this project adds to the knowledge surrounding VEGF and IGF-1 and their role in prostate cancer susceptibility. Importantly, this project has also introduced the potential role genetics plays in QoL, through investigating the relationships between genetic variants of VEGF and IGF-1 and QoL.

Sit versus stand : can sitting be accurately identified using MTI accelerometer data?

High levels of sitting have been linked with poor health outcomes. Previously a pragmatic MTI accelerometer data cut-point (100 count/min-1) has been used to estimate sitting. Data on the accuracy of this cut-point is unavailable. PURPOSE: To ascertain whether the 100 count/min-1 cut-point accurately isolates sitting from standing activities. METHODS: Participants fitted with an MTI accelerometer were observed performing a range of sitting, standing, light & moderate activities. 1-min epoch MTI data were matched to observed activities, then re-categorized as either sitting or not using the 100 count/min-1 cut-point. Self-report demographics and current physical activity were collected. Generalized estimating equation for repeated measures with a binary logistic model analyses (GEE), corrected for age, gender and BMI, were conducted to ascertain the odds of the MTI data being misclassified. RESULTS: Data were from 26 healthy subjects (8 men; 50% aged <25 years; mean BMI (SD) 22.7(3.8)m/kg2). MTI sitting and standing data mode was 0 count/min-1, with 46% of sitting activities and 21% of standing activities recording 0 count/min-1. The GEE was unable to accurately isolate sitting from standing activities using the 100 count/min-1 cut-point, since all sitting activities were incorrectly predicted as standing (p=0.05). To further explore the sensitivity of MTI data to delineate sitting from standing, the upper 95% confidence interval of the mean for the sitting activities (46 count/min-1) was used to re-categorise the data; this resulted in the GEE correctly classifying 49% of sitting, and 69% of standing activities. Using the 100 count/min-1 cut-point the data were re-categorised into a combined ‘sit/stand’ category and tested against other light activities: 88% of sit/stand and 87% of light activities were accurately predicted. Using Freedson’s moderate cut-point of 1952 count/min-1 the GEE accurately predicted 97% of light vs. 90% of moderate activities. CONCLUSION: The distributions of MTI recorded sitting and standing data overlap considerably, as such the 100 count/min -1 cut-point did not accurately isolate sitting from other static standing activities. The 100 count/min -1 cut-point more accurately predicted sit/stand vs. other movement orientated activities.

Arterial traffic congestion analysis using Bluetooth duration data

The aim of this study is to assess the potential use of Bluetooth data for traffic monitoring of arterial road networks. Bluetooth data provides the direct measurement of travel time between pairs of scanners, and intensive research has been reported on this topic. Bluetooth data includes “Duration” data, which represents the time spent by Bluetooth devices to pass through the detection range of Bluetooth scanners. If the scanners are located at signalised intersections, this Duration can be related to intersection performance, and hence represents valuable information for traffic monitoring. However the use of Duration has been ignored in previous analyses. In this study, the Duration data as well as travel time data is analysed to capture the traffic condition of a main arterial route in Brisbane. The data consists of one week of Bluetooth data provided by Brisbane City Council. As well, micro simulation analysis is conducted to further investigate the properties of Duration. The results reveal characteristics of Duration, and address future research needs to utilise this valuable data source.

A traffic simulation standard based on data marts

Traffic Simulation models tend to have their own data input and output formats. In an effort to standardise the input for traffic simulations, we introduce in this paper a set of data marts that aim to serve as a common interface between the necessaary data, stored in dedicated databases, and the swoftware packages, that require the input in a certain format. The data marts are developed based on real world objects (e.g. roads, traffic lights, controllers) rather than abstract models and hence contain all necessary information that can be transformed by the importing software package to their needs. The paper contains a full description of the data marts for network coding, simulation results, and scenario management, which have been discussed with industry partners to ensure sustainability.

Towards testing the eclectic paradigm on multinational contracting: an approach to reviewing and analysing secondary data

In response to the need to leverage private finance and the lack of competition in some parts of the Australian public sector major infrastructure market, especially in very large economic infrastructure procured using Pubic Private Partnerships, the Australian Federal government has demonstrated its desire to attract new sources of in-bound foreign direct investment (FDI) into the Australian construction market. This paper aims to report on progress towards an investigation into the determinants of multinational contractors’ willingness to bid for Australian public sector major infrastructure projects and which is designed to give an improved understanding of matters surrounding FDI into the Australian construction sector. This research deploys Dunning’s eclectic theory for the first time in terms of in-bound FDI by multinational contractors and as head contractors bidding for Australian major infrastructure public sector projects. Elsewhere, the authors have developed Dunning’s principal hypothesis associated with his eclectic framework in order to suit the context of this research and to address a weakness arising in Dunning’s principal hypothesis that is based on a nominal approach to the factors in the eclectic framework and which fail to speak to the relative explanatory power of these factors. In this paper, an approach to reviewing and analysing secondary data, as part of the first stage investigation in this research, is developed and some illustrations given, vis-à-vis the selected sector (roads, bridges and tunnels) in Australia (as the host location) and using one of the selected home countries (Spain). In conclusion, some tentative thoughts are offered in anticipation of the completion of the first stage investigation - in terms of the extent to which this first stage based on secondary data only might suggest the relative importance of the factors in the eclectic framework. It is noted that more robust conclusions are expected following the future planned stages of the research and these stages including primary data are briefly outlined. Finally, and beyond theoretical contributions expected from the overall approach taken to developing and testing Dunning’s framework, other expected contributions concerning research method and practical implications are mentioned.

Understanding the legal implications of data sharing, access and reuse in the Australian research landscape

Researchers are increasingly involved in data-intensive research projects that cut across geographic and disciplinary borders. Quality research now often involves virtual communities of researchers participating in large-scale web-based collaborations, opening their earlystage research to the research community in order to encourage broader participation and accelerate discoveries. The result of such large-scale collaborations has been the production of ever-increasing amounts of data. In short, we are in the midst of a data deluge. Accompanying these developments has been a growing recognition that if the benefits of enhanced access to research are to be realised, it will be necessary to develop the systems and services that enable data to be managed and secured. It has also become apparent that to achieve seamless access to data it is necessary not only to adopt appropriate technical standards, practices and architecture, but also to develop legal frameworks that facilitate access to and use of research data. This chapter provides an overview of the current research landscape in Australia as it relates to the collection, management and sharing of research data. The chapter then explains the Australian legal regimes relevant to data, including copyright, patent, privacy, confidentiality and contract law. Finally, this chapter proposes the infrastructure elements that are required for the proper management of legal interests, ownership rights and rights to access and use data collected or generated by research projects.

Feasibility of using health data sources to inform product safety surveillance in Queensland : a report for the Queensland Injury Prevention Council

This report provides an evaluation of the current available evidence-base for identification and surveillance of product-related injuries in children in Queensland. While the focal population was children in Queensland, the identification of information needs and data sources for product safety surveillance has applicability nationally for all age groups. The report firstly summarises the data needs of product safety regulators regarding product-related injury in children, describing the current sources of information informing product safety policy and practice, and documenting the priority product surveillance areas affecting children which have been a focus over recent years in Queensland. Health data sources in Queensland which have the potential to inform product safety surveillance initiatives were evaluated in terms of their ability to address the information needs of product safety regulators. Patterns in product-related injuries in children were analysed using routinely available health data to identify areas for future intervention, and the patterns in product-related injuries in children identified in health data were compared to those identified by product safety regulators. Recommendations were made for information system improvements and improved access to and utilisation of health data for more proactive approaches to product safety surveillance in the future.

Hunters & gatherers : strategies for curriculum mapping and data collection for assurance of learning

Assurance of learning is a predominant feature in both quality enhancement and assurance in higher education. Assurance of learning is a process that articulates explicit program outcomes and standards, and systematically gathers evidence to determine the extent to which performance matches expectations. Benefits accrue to the institution through the systematic assessment of whole of program goals. Data may be used for continuous improvement, program development, and to inform external accreditation and evaluation bodies. Recent developments, including the introduction of the Tertiary Education and Quality Standards Agency (TEQSA) will require universities to review the methods they use to assure learning outcomes. This project investigates two critical elements of assurance of learning: 1. the mapping of graduate attributes throughout a program; and 2. the collection of assurance of learning data. An audit was conducted with 25 of the 39 Business Schools in Australian universities to identify current methods of mapping graduate attributes and for collecting assurance of learning data across degree programs, as well as a review of the key challenges faced in these areas. Our findings indicate that external drivers like professional body accreditation (for example: Association to Advance Collegiate Schools of Business (AACSB)) and TEQSA are important motivators for assuring learning, and those who were undertaking AACSB accreditation had more robust assurance of learning systems in place. It was reassuring to see that the majority of institutions (96%) had adopted an embedding approach to assuring learning rather than opting for independent standardised testing. The main challenges that were evident were the development of sustainable processes that were not considered a burden to academic staff, and obtainment of academic buy in to the benefits of assuring learning per se rather than assurance of learning being seen as a tick box exercise. This cultural change is the real challenge in assurance of learning practice.

Data modelling in the beginning school years

This paper argues for a renewed focus on statistical reasoning in the beginning school years, with opportunities for children to engage in data modelling. Some of the core components of data modelling are addressed. A selection of results from the first data modelling activity implemented during the second year (2010; second grade) of a current longitudinal study are reported. Data modelling involves investigations of meaningful phenomena, deciding what is worthy of attention (identifying complex attributes), and then progressing to organising, structuring, visualising, and representing data. Reported here are children's abilities to identify diverse and complex attributes, sort and classify data in different ways, and create and interpret models to represent their data.

The influence of ambient temperature on birth outcomes in Brisbane, Australia

Lately, there has been increasing interest in the association between temperature and adverse birth outcomes including preterm birth (PTB) and stillbirth. PTB is a major predictor of many diseases later in life, and stillbirth is a devastating event for parents and families. The aim of this study was to assess the seasonal pattern of adverse birth outcomes, and to examine possible associations of maternal exposure to temperature with PTB and stillbirth. We also aimed to identify if there were any periods of the pregnancy where exposure to temperature was particularly harmful. A retrospective cohort study design was used and we retrieved individual birth records from the Queensland Health Perinatal Data Collection Unit for all singleton births (excluding twins and triplets) delivered in Brisbane between 1 July 2005 and 30 June 2009. We obtained weather data (including hourly relative humidity, minimum and maximum temperature) and air-pollution data (including PM10, SO2 and O3) from the Queensland Department of Environment and Resource Management. We used survival analyses with the time-dependent variables of temperature, humidity and air pollution, and the competing risks of stillbirth and live birth. To assess the monthly pattern of the birth outcomes, we fitted month of pregnancy as a time-dependent variable. We examined the seasonal pattern of the birth outcomes and the relationship between exposure to high or low temperatures and birth outcomes over the four lag weeks before birth. We further stratified by categorisation of PTB: extreme PTB (< 28 weeks of gestation), PTB (28–36 weeks of gestation), and term birth (≥ 37 weeks of gestation). Lastly, we examined the effect of temperature variation in each week of the pregnancy on birth outcomes. There was a bimodal seasonal pattern in gestation length. After adjusting for temperature, the seasonal pattern changed from bimodal, to only one peak in winter. The risk of stillbirth was statistically significant lower in March compared with January. After adjusting for temperature, the March trough was still statistically significant and there was a peak in risk (not statistically significant) in winter. There was an acute effect of temperature on gestational age and stillbirth with a shortened gestation for increasing temperature from 15 °C to 25 °C over the last four weeks before birth. For stillbirth, we found an increasing risk with increasing temperatures from 12 °C to approximately 20 °C, and no change in risk at temperatures above 20 °C. Certain periods of the pregnancy were more vulnerable to temperature variation. The risk of PTB (28–36 weeks of gestation) increased as temperatures increased above 21 °C. For stillbirth, the fetus was most vulnerable at less than 28 weeks of gestation, but there were also effects in 28–36 weeks of gestation. For fetuses of more than 37 weeks of gestation, increasing temperatures did not increase the risk of stillbirth. We did not find any adverse affects of cold temperature on birth outcomes in this cohort. My findings contribute to knowledge of the relationship between temperature and birth outcomes. In the context of climate change, this is particularly important. The results may have implications for public health policy and planning, as they indicate that pregnant women would decrease their risk of adverse birth outcomes by avoiding exposure to high temperatures and seeking cool environments during hot days.

Modulation of the Chlamydia trachomatis In vitro transcriptome response by the sex hormones estradiol and progesterone

BACKGROUND:Chlamydia trachomatis is a major cause of sexually transmitted disease in humans. Previous studies in both humans and animal models of chlamydial genital tract infection have suggested that the hormonal status of the genital tract epithelium at the time of exposure can influence the outcome of the chlamydial infection. We performed a whole genome transcriptional profiling study of C. trachomatis infection in ECC-1 cells under progesterone or estradiol treatment.RESULTS:Both hormone treatments caused a significant shift in the sub-set of genes expressed (25% of the transcriptome altered by more than 2-fold). Overall, estradiol treatment resulted in the down-regulation of 151 genes, including those associated with lipid and nucleotide metabolism. Of particular interest was the up-regulation in estradiol-supplemented cultures of six genes (omcB, trpB, cydA, cydB, pyk and yggV), which suggest a stress response similar to that reported previously in other models of chlamydial persistence. We also observed morphological changes consistent with a persistence response. By comparison, progesterone supplementation resulted in a general up-regulation of an energy utilising response.CONCLUSION:Our data shows for the first time, that the treatment of chlamydial host cells with key reproductive hormones such as progesterone and estradiol, results in significantly altered chlamydial gene expression profiles. It is likely that these chlamydial expression patterns are survival responses, evolved by the pathogen to enable it to overcome the host's innate immune response. The induction of chlamydial persistence is probably a key component of this survival response.