Text mining with semantic annotation : using enriched text representation for entity-oriented retrieval, semantic relation identification and text clustering

This project is a step forward in the study of text mining where enhanced text representation with semantic information plays a significant role. It develops effective methods of entity-oriented retrieval, semantic relation identification and text clustering utilizing semantically annotated data. These methods are based on enriched text representation generated by introducing semantic information extracted from Wikipedia into the input text data. The proposed methods are evaluated against several start-of-art benchmarking methods on real-life data-sets. In particular, this thesis improves the performance of entity-oriented retrieval, identifies different lexical forms for an entity relation and handles clustering documents with multiple feature spaces.

Fouling of waste heat recovery : numerical and experimental results

Numerical results are presented to investigate the performance of a partly-filled porous heat exchanger for waste heat recovery units. A parametric study was conducted to investigate the effects of inlet velocity and porous block height on the pressure drop of the heat exchanger. The focus of this work is on modelling the interface of a porous and non-porous region. As such, numerical simulation of the problem is conducted along with hot-wire measurements to better understand the physics of the problem. Results from the two sources are then compared to existing theoretical predictions available in the literature which are unable to predict the existence of two separation regions before and after the porous block. More interestingly, a non-uniform interface velocity was observed along the streamwise direction based on both numerical and experimental data.

Health consequences of exposure to e-waste : a systematic review

Background The population exposed to potentially hazardous substances through inappropriate and unsafe management practices related to disposal and recycling of end-of-life electrical and electronic equipment, collectively known as e-waste, is increasing. We aimed to summarise the evidence for the association between such exposures and adverse health outcomes. Methods We systematically searched five electronic databases (PubMed, Embase, Web of Science, PsycNET, and CINAHL) for studies assessing the association between exposure to e-waste and outcomes related to mental health and neurodevelopment, physical health, education, and violence and criminal behaviour, from Jan 1, 1965, to Dec 17, 2012, and yielded 2274 records. Of the 165 full-text articles assessed for eligibility, we excluded a further 142, resulting in the inclusion of 23 published epidemiological studies that met the predetermined criteria. All studies were from southeast China. We assessed evidence of a causal association between exposure to e-waste and health outcomes within the Bradford Hill framework. Findings We recorded plausible outcomes associated with exposure to e-waste including change in thyroid function, changes in cellular expression and function, adverse neonatal outcomes, changes in temperament and behaviour, and decreased lung function. Boys aged 8–9 years living in an e-waste recycling town had a lower forced vital capacity than did those living in a control town. Significant negative correlations between blood chromium concentrations and forced vital capacity in children aged 11 and 13 years were also reported. Findings from most studies showed increases in spontaneous abortions, stillbirths, and premature births, and reduced birthweights and birth lengths associated with exposure to e-waste. People living in e-waste recycling towns or working in e-waste recycling had evidence of greater DNA damage than did those living in control towns. Studies of the effects of exposure to e-waste on thyroid function were not consistent. One study related exposure to e-waste and waste electrical and electronic equipment to educational outcomes. Interpretation Although data suggest that exposure to e-waste is harmful to health, more well designed epidemiological investigations in vulnerable populations, especially pregnant women and children, are needed to confirm these associations. Funding Children's Health and Environment Program, Queensland Children's Medical Research Institute, The University of Queensland, Australia.

Compositional data analysis (CoDA) approaches to distance in information retrieval

Many techniques in information retrieval produce counts from a sample, and it is common to analyse these counts as proportions of the whole - term frequencies are a familiar example. Proportions carry only relative information and are not free to vary independently of one another: for the proportion of one term to increase, one or more others must decrease. These constraints are hallmarks of compositional data. While there has long been discussion in other fields of how such data should be analysed, to our knowledge, Compositional Data Analysis (CoDA) has not been considered in IR. In this work we explore compositional data in IR through the lens of distance measures, and demonstrate that common measures, naïve to compositions, have some undesirable properties which can be avoided with composition-aware measures. As a practical example, these measures are shown to improve clustering. Copyright 2014 ACM.

Bio-hydrogen production from food waste through anaerobic fermentation

In order to protect our planet and ourselves from the adverse effects of excessive CO2 emissions and to prevent an imminent non-renewable fossil fuel shortage and energy crisis, there is a need to transform our current ‘fossil fuel dependent’ energy systems to new, clean, renewable energy sources. The world has recognized hydrogen as an energy carrier that complies with all the environmental quality and energy security, demands. This research aimed at producing hydrogen through anaerobic fermentation, using food waste as the substrate. Four food waste substrates were used: Rice, fish, vegetable and their mixture. Bio-hydrogen production was performed in lab scale reactors, using 250 mL serum bottles. The food waste was first mixed with the anaerobic sewage sludge and incubated at 37°C for 31 days (acclimatization). The anaerobic sewage sludge was then heat treated at 80°C for 15 min. The experiment was conducted at an initial pH of 5.5 and temperatures of 27, 35 and 55°C. The maximum cumulative hydrogen produced by rice, fish, vegetable and mixed food waste substrates were highest at 37°C (Rice =26.97±0.76 mL, fish = 89.70±1.25 mL, vegetable = 42.00±1.76 mL, mixed = 108.90±1.42 mL). A comparative study of acclimatized (the different food waste substrates were mixed with anaerobic sewage sludge and incubated at 37°C for 31days) and non-acclimatized food waste substrate (food waste that was not incubated with anaerobic sewage sludge) showed that acclimatized food waste substrate enhanced bio-hydrogen production by 90 - 100%.

Smart phones and tablets in the early years : a waste of time or a valuable opportunity for accessing information and communicating?

New digital media surrounds us. Little is known, however, about the influence of technology devices such as tablets (e.g. iPads) and smart phones on young children’s lives in home and school settings, and what it means for them throughout their schooling and beyond. Most research to date has focused on children aged six years and older, and much less (with a few exceptions) on preschool-aged children. This article draws on parent interviews to show how family members engage with technology as part of the flow of everyday life. Only time and increased understandings of everyday practices will tell the real values and scope of using digital media.

Mobile interaction design approaches for reducing domestic food waste

This thesis is a trans-disciplinary study of domestic food waste in Australia. Firstly, it examines why consumers are prone to waste food. Secondly, it explores several situated design interventions to reduce domestic food waste by informing consumer food supply and location awareness, and improving the level of food literacy among consumers. The thesis outcomes have implications for academic and industry domains within the fields of Human-Computer Interaction, urban informatics, environmental sustainability, food security and public health.

Bioaerosols associated with industrial green waste composting facilities and optimal microbiological indicators

This project developed and assessed a standard operating procedure for monitoring microbiological aerosol levels and dispersal from Australian industrial composting facilities. Development occurred via seasonal monitoring of such operations with evaluation of optimal microbial indicator organisms, sampling and analysis logistics. The resultant procedure allows practical end-user assessment of compost-associated bioaerosol levels, and potential health risks to proximal residential populations encroaching on such composting facilities and on-site industrial operations personnel.

Pattern-based topic modelling and its application for information filtering and information retrieval

This thesis targets on a challenging issue that is to enhance users' experience over massive and overloaded web information. The novel pattern-based topic model proposed in this thesis can generate high-quality multi-topic user interest models technically by incorporating statistical topic modelling and pattern mining. We have successfully applied the pattern-based topic model to both fields of information filtering and information retrieval. The success of the proposed model in finding the most relevant information to users mainly comes from its precisely semantic representations to represent documents and also accurate classification of the topics at both document level and collection level.

How everyday language can and will boost effective information retrieval

Typing 2 or 3 keywords into a browser has become an easy and efficient way to find information. Yet, typing even short queries becomes tedious on ever shrinking (virtual) keyboards. Meanwhile, speech processing is maturing rapidly, facilitating everyday language input. Also, wearable technology can inform users proactively by listening in on their conversations or processing their social media interactions. Given these developments, everyday language may soon become the new input of choice. We present an information retrieval (IR) algorithm specifically designed to accept everyday language. It integrates two paradigms of information retrieval, previously studied in isolation; one directed mainly at the surface structure of language, the other primarily at the underlying meaning. The integration was achieved by a Markov machine that encodes meaning by its transition graph, and surface structure by the language it generates. A rigorous evaluation of the approach showed, first, that it can compete with the quality of existing language models, second, that it is more effective the more verbose the input, and third, as a consequence, that it is promising for an imminent transition from keyword input, where the onus is on the user to formulate concise queries, to a modality where users can express more freely, more informal, and more natural their need for information in everyday language.