Building climate change resilience and adaptive capacity in Australia’s community sector using social media and technology innovation

Public and private sector organisations worldwide are putting strategies in place to manage the commercial and operational risks of climate change. However, community organisations are lagging behind in their understanding and preparedness, despite them being among the most exposed to the effects of climate change impacts and regulation. This poster presents a proposal for a multidisciplinary study that addresses this issue by developing, testing and applying a novel climate risk assessment methodology that is tailored to the needs of Australia’s community sector and its clients. Strategies to mitigate risks and build resilience and adaptive capacity will be identified including new opportunities afforded by urban informatics, social media, and technologies of scale making.

Coordinated research support services at Queensland University of Technology, Australia

Queensland University of Technology (QUT) is a large multidisciplinary university located in Brisbane, Queensland, Australia. QUT is increasing its research focus and is developing its research support services. It has adopted a model of collaboration between the Library, High Performance Computing and Research Support (HPC) and more broadly with Information Technology Services (ITS). Research support services provided by the Library include the provision of information resources and discovery services, bibliographic management software, assistance with publishing (publishing strategies, identifying high impact journals, dealing with publishers and the peer review process), citation analysis and calculating authors’ H Index. Research data management services are being developed by the Library and HPC working in collaboration. The HPC group within ITS supports research computing infrastructure, research development and engagement activities, researcher consultation, high speed computation and data storage systems , 2D/ 3D (immersive) visualisation tools, parallelisation and optimization of research codes, statistics/ data modeling training and support (both qualitative and quantitative) and support for the university’s central Access Grid collaboration facility. Development and engagement activities include participation in research grants and papers, student supervision and internships and the sponsorship, incubation and adoption of new computing technologies for research. ITS also provides other services that support research including ICT training, research infrastructure (networking, data storage, federated access and authorization, virtualization) and corporate systems for research administration. Seminars and workshops are offered to increase awareness and uptake of new and existing services. A series of online surveys on eResearch practices and skills and a number of focus groups was conducted to better inform the development of research support services. Progress towards the provision of research support is described within the context organizational frameworks; resourcing; infrastructure; integration; collaboration; change management; engagement; awareness and skills; new services; and leadership. Challenges to be addressed include the need to redeploy existing operational resources toward new research support services, supporting a rapidly growing research profile across the university, the growing need for the use and support of IT in research programs, finding capacity to address the diverse research support needs across the disciplines, operationalising new research support services following their implementation in project mode, embedding new specialist staff roles, cross-skilling Liaison Librarians, and ensuring continued collaboration between stakeholders.

Design optimisation using advanced artificial intelligent system coupled to hybrid-game strategies

One of the main aims in artificial intelligent system is to develop robust and efficient optimisation methods for Multi-Objective (MO) and Multidisciplinary Design (MDO) design problems. The paper investigates two different optimisation techniques for multi-objective design optimisation problems. The first optimisation method is a Non-Dominated Sorting Genetic Algorithm II (NSGA-II). The second method combines the concepts of Nash-equilibrium and Pareto optimality with Multi-Objective Evolutionary Algorithms (MOEAs) which is denoted as Hybrid-Game. Numerical results from the two approaches are compared in terms of the quality of model and computational expense. The benefit of using the distributed hybrid game methodology for multi-objective design problems is demonstrated.

Licensing technology : negotiating and drafting technology transfer agreements [3rd ed.]

Part I of this book covers the commercial and contractual background to technology licensing agreements. Part II discusses the European Community's new regime on the application and enforcement of Article 81 to technology licensing agreements. EC Council Regulation 1/2003 replaced the Council Regulation 17/1962 and repealed the system under which restrictive agreements and practices could be notified to the EC Commission. A new Commission regulation on technology transfer agreements, Regulation 772/2004. These two enactments required consequential amendments to the chapters in Part III where the usual terms of technology licensing agreements are analysed and exemplified by reference to decided cases.

An application of near-infrared and mid-infrared spectroscopy to the study of natural halotrichites : halotrichite, apjohnite and wupatkiite

Near-infrared (NIR) and Fourier transform infrared (FTIR) spectroscopy have been used to determine the mineralogical character of isomorphic substitutions for Mg2+ by divalent transition metals Fe, Mn, Co and Ni in natural halotrichite series. The minerals are characterised by d-d transitions in NIR region 12000-7500 cm-1. NIR spectrum of halotrichite reveals broad feature from 12000 to 7500 cm-1 with a splitting of two bands resulting from ferrous ion transition 5T2g ® 5Eg. The presence of overtones of OH- fundamentals near 7000 cm-1 confirms molecular water in the mineral structure of the halotrichite series. The appearance of the most intense peak at around 5132 cm-1 is a common feature in the three minerals and is derived from combination of OH- vibrations of water molecules and 2 water bending modes. The influence of cations like Mg2+, Fe2+, Mn2+, Co2+, Ni2+ shows on the spectra of halotrichites. Especially wupatkiite-OH stretching vibrations in which bands are distorted conspicuously to low wave numbers at 3270, 2904 and 2454 cm-1. The observation of high frequency 2 mode in the infrared spectrum at 1640 cm-1 indicates coordination of water molecules is strongly hydrogen bonded in natural halotrichites. The splittings of bands in 3 and 4 (SO4)2- stretching regions may be attributed to the reduction of symmetry from Td to C2v for sulphate ion. This work has shown the usefulness of NIR spectroscopy for the rapid identification and classification of the halotrichite minerals.

Life in the 'real world': a profile of Queensland University of Technology Library and Information Science graduates.

A graduate destination survey can provide a snap shot in time of a graduate’s career progression and outcome. This paper will present the results of a Queensland University of Technology study exploring the employment outcomes of students who had completed a library and information science course from the Faculty of Information Technology between 2000 and 2008. Seventy-four graduates completed an online questionnaire administered in July 2009. The study found that 90% of the graduates surveyed were working and living in Queensland, with over three quarters living and working in Brisbane. Nearly 70% were working full-time, while only 1.4% indicating that they were unemployed and looking for work. Over 80% of the graduates identified themselves as working in “librarianship”. This study is the first step in understanding the progression and destination of QUT’s library and information science graduates. It is recommended that this survey becomes an ongoing initiative so that the results can be analysed and compared over time.

Performance analysis of unified enterprise application security framework

Unified Enterprise application security is a new emerging approach for providing protection against application level attacks. Conventional application security approach that consists of embedding security into each critical application leads towards scattered security mechanism that is not only difficult to manage but also creates security loopholes. According to the CSIIFBI computer crime survey report, almost 80% of the security breaches come from authorized users. In this paper, we have worked on the concept of unified security model, which manages all security aspect from a single security window. The basic idea is to keep business functionality separate from security components of the application. Our main focus was on the designing of frame work for unified layer which supports single point of policy control, centralize logging mechanism, granular, context aware access control, and independent from any underlying authentication technology and authorization policy.

secFleck: A Public Key Technology Platform for Wireless Sensor Networks

We describe the design and implementation of a public-key platform, secFleck, based on a commodity Trusted Platform Module (TPM) chip that extends the capability of a standard node. Unlike previous software public-key implementations this approach provides E- Commerce grade security; is computationally fast, energy efficient; and has low financial cost — all essential attributes for secure large-scale sen- sor networks. We describe the secFleck message security services such as confidentiality, authenticity and integrity, and present performance re- sults including computation time, energy consumption and cost. This is followed by examples, built on secFleck, of symmetric key management, secure RPC and secure software update.

The Application of wireless LANS in mine automation

The objective of this paper is to provide an overview of mine automation applications, developed at the Queensland Centre for Advanced Technology (QCAT), which make use of IEEE 802.11b wireless local area networks (WLANs). The paper has been prepared for a 2002 conference entitled "Creating the Virtual Enterprise - Leveraging wireless technology within existing business models for corporate advantage". Descriptions of the WLAN components have been omitted here as such details are presented in the accompanying papers. The structure of the paper is as follows. Application overviews are provided in Sections 2 to 7. Some pertinent strengths and weaknesses are summarised in Section 8. Please refer to http://www.mining-automation.com/ or contact the authors for further information.

Access to public sector information : law, technology and policy

On the back of the growing capacity of networked digital information technologies to process and visualise large amounts of information in a timely, efficient and user-driven manner we have seen an increasing demand for better access to and re-use of public sector information (PSI). The story is not a new one. Share knowledge and together we can do great things; limit access and we reduce the potential for opportunity. The two volumes of this book seek to explain and analyse this global shift in the way we manage public sector information. In doing so they collect and present papers, reports and submissions on the topic by leading authors and institutions from across the world. These in turn provide people tasked with mapping out and implementing information policy with reference material and practical guidance. Volume 1 draws together papers on the topic by policymakers, academics and practitioners while Volume 2 presents a selection of the key reports and submissions that have been published over the last few years.

Application of data mining techniques in the prediction of coronary artery disease : use of anaesthesia time-series and patient risk factor data

The high morbidity and mortality associated with atherosclerotic coronary vascular disease (CVD) and its complications are being lessened by the increased knowledge of risk factors, effective preventative measures and proven therapeutic interventions. However, significant CVD morbidity remains and sudden cardiac death continues to be a presenting feature for some subsequently diagnosed with CVD. Coronary vascular disease is also the leading cause of anaesthesia related complications. Stress electrocardiography/exercise testing is predictive of 10 year risk of CVD events and the cardiovascular variables used to score this test are monitored peri-operatively. Similar physiological time-series datasets are being subjected to data mining methods for the prediction of medical diagnoses and outcomes. This study aims to find predictors of CVD using anaesthesia time-series data and patient risk factor data. Several pre-processing and predictive data mining methods are applied to this data. Physiological time-series data related to anaesthetic procedures are subjected to pre-processing methods for removal of outliers, calculation of moving averages as well as data summarisation and data abstraction methods. Feature selection methods of both wrapper and filter types are applied to derived physiological time-series variable sets alone and to the same variables combined with risk factor variables. The ability of these methods to identify subsets of highly correlated but non-redundant variables is assessed. The major dataset is derived from the entire anaesthesia population and subsets of this population are considered to be at increased anaesthesia risk based on their need for more intensive monitoring (invasive haemodynamic monitoring and additional ECG leads). Because of the unbalanced class distribution in the data, majority class under-sampling and Kappa statistic together with misclassification rate and area under the ROC curve (AUC) are used for evaluation of models generated using different prediction algorithms. The performance based on models derived from feature reduced datasets reveal the filter method, Cfs subset evaluation, to be most consistently effective although Consistency derived subsets tended to slightly increased accuracy but markedly increased complexity. The use of misclassification rate (MR) for model performance evaluation is influenced by class distribution. This could be eliminated by consideration of the AUC or Kappa statistic as well by evaluation of subsets with under-sampled majority class. The noise and outlier removal pre-processing methods produced models with MR ranging from 10.69 to 12.62 with the lowest value being for data from which both outliers and noise were removed (MR 10.69). For the raw time-series dataset, MR is 12.34. Feature selection results in reduction in MR to 9.8 to 10.16 with time segmented summary data (dataset F) MR being 9.8 and raw time-series summary data (dataset A) being 9.92. However, for all time-series only based datasets, the complexity is high. For most pre-processing methods, Cfs could identify a subset of correlated and non-redundant variables from the time-series alone datasets but models derived from these subsets are of one leaf only. MR values are consistent with class distribution in the subset folds evaluated in the n-cross validation method. For models based on Cfs selected time-series derived and risk factor (RF) variables, the MR ranges from 8.83 to 10.36 with dataset RF_A (raw time-series data and RF) being 8.85 and dataset RF_F (time segmented time-series variables and RF) being 9.09. The models based on counts of outliers and counts of data points outside normal range (Dataset RF_E) and derived variables based on time series transformed using Symbolic Aggregate Approximation (SAX) with associated time-series pattern cluster membership (Dataset RF_ G) perform the least well with MR of 10.25 and 10.36 respectively. For coronary vascular disease prediction, nearest neighbour (NNge) and the support vector machine based method, SMO, have the highest MR of 10.1 and 10.28 while logistic regression (LR) and the decision tree (DT) method, J48, have MR of 8.85 and 9.0 respectively. DT rules are most comprehensible and clinically relevant. The predictive accuracy increase achieved by addition of risk factor variables to time-series variable based models is significant. The addition of time-series derived variables to models based on risk factor variables alone is associated with a trend to improved performance. Data mining of feature reduced, anaesthesia time-series variables together with risk factor variables can produce compact and moderately accurate models able to predict coronary vascular disease. Decision tree analysis of time-series data combined with risk factor variables yields rules which are more accurate than models based on time-series data alone. The limited additional value provided by electrocardiographic variables when compared to use of risk factors alone is similar to recent suggestions that exercise electrocardiography (exECG) under standardised conditions has limited additional diagnostic value over risk factor analysis and symptom pattern. The effect of the pre-processing used in this study had limited effect when time-series variables and risk factor variables are used as model input. In the absence of risk factor input, the use of time-series variables after outlier removal and time series variables based on physiological variable values’ being outside the accepted normal range is associated with some improvement in model performance.

The application of phonetic distribution normalisation to likelihood-maximising speech enhancement for robust ASR

Traditional speech enhancement methods optimise signal-level criteria such as signal-to-noise ratio, but such approaches are sub-optimal for noise-robust speech recognition. Likelihood-maximising (LIMA) frameworks on the other hand, optimise the parameters of speech enhancement algorithms based on state sequences generated by a speech recogniser for utterances of known transcriptions. Previous applications of LIMA frameworks have generated a set of global enhancement parameters for all model states without taking in account the distribution of model occurrence, making optimisation susceptible to favouring frequently occurring models, in particular silence. In this paper, we demonstrate the existence of highly disproportionate phonetic distributions on two corpora with distinct speech tasks, and propose to normalise the influence of each phone based on a priori occurrence probabilities. Likelihood analysis and speech recognition experiments verify this approach for improving ASR performance in noisy environments.

An initial technology roadmap for home automation : home and personal life management

Home Automation (HA) has emerged as a prominent ¯eld for researchers and in- vestors confronting the challenge of penetrating the average home user market with products and services emerging from technology based vision. In spite of many technology contri- butions, there is a latent demand for a®ordable and pragmatic assistive technologies for pro-active handling of complex lifestyle related problems faced by home users. This study has pioneered to develop an Initial Technology Roadmap for HA (ITRHA) that formulates a need based vision of 10-15 years, identifying market, product and technology investment opportunities, focusing on those aspects of HA contributing to e±cient management of home and personal life. The concept of Family Life Cycle is developed to understand the temporal needs of family. In order to formally describe a coherent set of family processes, their relationships, and interaction with external elements, a reference model named Fam- ily System is established that identi¯es External Entities, 7 major Family Processes, and 7 subsystems-Finance, Meals, Health, Education, Career, Housing, and Socialisation. Anal- ysis of these subsystems reveals Soft, Hard and Hybrid processes. Rectifying the lack of formal methods for eliciting future user requirements and reassessing evolving market needs, this study has developed a novel method called Requirement Elicitation of Future Users by Systems Scenario (REFUSS), integrating process modelling, and scenario technique within the framework of roadmapping. The REFUSS is used to systematically derive process au- tomation needs relating the process knowledge to future user characteristics identi¯ed from scenarios created to visualise di®erent futures with richly detailed information on lifestyle trends thus enabling learning about the future requirements. Revealing an addressable market size estimate of billions of dollars per annum this research has developed innovative ideas on software based products including Document Management Systems facilitating automated collection, easy retrieval of all documents, In- formation Management System automating information services and Ubiquitous Intelligent System empowering the highly mobile home users with ambient intelligence. Other product ideas include robotic devices of versatile Kitchen Hand and Cleaner Arm that can be time saving. Materialisation of these products require technology investment initiating further research in areas of data extraction, and information integration as well as manipulation and perception, sensor actuator system, tactile sensing, odour detection, and robotic controller. This study recommends new policies on electronic data delivery from service providers as well as new standards on XML based document structure and format.

Physiological investigation of periosteum structure and its application in periosteum tissue engineering

Although many different materials, techniques and methods, including artificial or engineered bone substitutes, have been used to repair various bone defects, the restoration of critical-sized bone defects caused by trauma, surgery or congenital malformation is still a great challenge to orthopedic surgeons. One important fact that has been neglected in the pursuit of resolutions for large bone defect healing is that most physiological bone defect healing needs the periosteum and stripping off the periosteum may result in non-union or non-healed bone defects. Periosteum plays very important roles not only in bone development but also in bone defect healing. The purpose of this project was to construct a functional periosteum in vitro using a single stem cell source and then test its ability to aid the repair of critical-sized bone defect in animal models. This project was designed with three separate but closely-linked parts which in the end led to four independent papers. The first part of this study investigated the structural and cellular features in periostea from diaphyseal and metaphyseal bone surfaces in rats of different ages or with osteoporosis. Histological and immunohistological methods were used in this part of the study. Results revealed that the structure and cell populations in periosteum are both age-related and site-specific. The diaphyseal periosteum showed age-related degeneration, whereas the metaphyseal periosteum is more destructive in older aged rats. The periosteum from osteoporotic bones differs from normal bones both in terms of structure and cell populations. This is especially evident in the cambial layer of the metaphyseal area. Bone resorption appears to be more active in the periosteum from osteoporotic bones, whereas bone formation activity is comparable between the osteoporotic and normal bone. The dysregulation of bone resorption and formation in the periosteum may also be the effect of the interaction between various neural pathways and the cell populations residing within it. One of the most important aspects in periosteum engineering is how to introduce new blood vessels into the engineered periosteum to help form vascularized bone tissues in bone defect areas. The second part of this study was designed to investigate the possibility of differentiating bone marrow stromal cells (BMSCs) into the endothelial cells and using them to construct vascularized periosteum. The endothelial cell differentiation of BMSCs was induced in pro-angiogenic media under both normoxia and CoCl2 (hypoxia-mimicking agent)-induced hypoxia conditions. The VEGF/PEDF expression pattern, endothelial cell specific marker expression, in vitro and in vivo vascularization ability of BMSCs cultured in different situations were assessed. Results revealed that BMSCs most likely cannot be differentiated into endothelial cells through the application of pro-angiogenic growth factors or by culturing under CoCl2-induced hypoxic conditions. However, they may be involved in angiogenesis as regulators under both normoxia and hypoxia conditions. Two major angiogenesis-related growth factors, VEGF (pro-angiogenic) and PEDF (anti-angiogenic) were found to have altered their expressions in accordance with the extracellular environment. BMSCs treated with the hypoxia-mimicking agent CoCl2 expressed more VEGF and less PEDF and enhanced the vascularization of subcutaneous implants in vivo. Based on the findings of the second part, the CoCl2 pre-treated BMSCs were used to construct periosteum, and the in vivo vascularization and osteogenesis of the constructed periosteum were assessed in the third part of this project. The findings of the third part revealed that BMSCs pre-treated with CoCl2 could enhance both ectopic and orthotopic osteogenesis of BMSCs-derived osteoblasts and vascularization at the early osteogenic stage, and the endothelial cells (HUVECs), which were used as positive control, were only capable of promoting osteogenesis after four-weeks. The subcutaneous area of the mouse is most likely inappropriate for assessing new bone formation on collagen scaffolds. This study demonstrated the potential application of CoCl2 pre-treated BMSCs in the tissue engineering not only for periosteum but also bone or other vascularized tissues. In summary, the structure and cell populations in periosteum are age-related, site-specific and closely linked with bone health status. BMSCs as a stem cell source for periosteum engineering are not endothelial cell progenitors but regulators, and CoCl2-treated BMSCs expressed more VEGF and less PEDF. These CoCl2-treated BMSCs enhanced both vascularization and osteogenesis in constructed periosteum transplanted in vivo.

Developing a theatre of the integrated actor : the application of the Suzuki actor training method within three theatrical contexts

This research project examines the application of the Suzuki Actor Training Method (the Suzuki Method) within the work ofTadashi Suzuki's company in Japan, the Shizuoka Performing Arts Complex (SPAC), within the work of Brisbane theatre company Frank:Austral Asian Performance Ensemble (Frank:AAPE), and as related to the development of the theatre performance Surfacing. These three theatrical contexts have been studied from the viewpoint of a "participant- observer". The researcher has trained in the Suzuki Method with Frank:AAPE and SP AC, performed with Frank:AAPE, and was the solo performer and collaborative developer in the performance Surfacing (directed by Leah Mercer). Observations of these three groups are based on a phenomenological definition of the "integrated actor", an actor who is able to achieve a totality or unity between the body and the mind, and between the body and the voice, through a powerful sense of intention. The term "integrated actor" has been informed by the philosophy of Merleau-Ponty and his concept of the "lived body". Three main hypotheses are presented in this study: that the Suzuki Method focuses on actors learning through their body; that the Suzuki Method presents an holistic approach to the body and the voice; and that the Suzuki Method develops actors with a strong sense of intention. These three aspects of the Suzuki Method are explored in relation to the stylistic features of the work of SPAC, Frank:AAPE and the performance Surfacing.