Analysis of acoustic emission data for structural health monitoring applications

Acoustic emission (AE) is the phenomenon where high frequency stress waves are generated by rapid release of energy within a material by sources such as crack initiation or growth. AE technique involves recording these stress waves by means of sensors placed on the surface and subsequent analysis of the recorded signals to gather information such as the nature and location of the source. It is one of the several diagnostic techniques currently used for structural health monitoring (SHM) of civil infrastructure such as bridges. Some of its advantages include ability to provide continuous in-situ monitoring and high sensitivity to crack activity. But several challenges still exist. Due to high sampling rate required for data capture, large amount of data is generated during AE testing. This is further complicated by the presence of a number of spurious sources that can produce AE signals which can then mask desired signals. Hence, an effective data analysis strategy is needed to achieve source discrimination. This also becomes important for long term monitoring applications in order to avoid massive date overload. Analysis of frequency contents of recorded AE signals together with the use of pattern recognition algorithms are some of the advanced and promising data analysis approaches for source discrimination. This paper explores the use of various signal processing tools for analysis of experimental data, with an overall aim of finding an improved method for source identification and discrimination, with particular focus on monitoring of steel bridges.

The Early Prevention of Obesity in CHildren (EPOCH) collaboration : an individual patient data prospective meta-analysis

Background: Efforts to prevent the development of overweight and obesity have increasingly focused early in the life course as we recognise that both metabolic and behavioural patterns are often established within the first few years of life. Randomised controlled trials (RCTs) of interventions are even more powerful when, with forethought, they are synthesised into an individual patient data (IPD) prospective meta-analysis (PMA). An IPD PMA is a unique research design where several trials are identified for inclusion in an analysis before any of the individual trial results become known and the data are provided for each randomised patient. This methodology minimises the publication and selection bias often associated with a retrospective meta-analysis by allowing hypotheses, analysis methods and selection criteria to be specified a priori. Methods/Design: The Early Prevention of Obesity in CHildren (EPOCH) Collaboration was formed in 2009. The main objective of the EPOCH Collaboration is to determine if early intervention for childhood obesity impacts on body mass index (BMI) z scores at age 18-24 months. Additional research questions will focus on whether early intervention has an impact on children’s dietary quality, TV viewing time, duration of breastfeeding and parenting styles. This protocol includes the hypotheses, inclusion criteria and outcome measures to be used in the IPD PMA. The sample size of the combined dataset at final outcome assessment (approximately 1800 infants) will allow greater precision when exploring differences in the effect of early intervention with respect to pre-specified participant- and intervention-level characteristics. Discussion: Finalisation of the data collection procedures and analysis plans will be complete by the end of 2010. Data collection and analysis will occur during 2011-2012 and results should be available by 2013. Trial registration number: ACTRN12610000789066

The Guardian reportage of the UK MP expenses scandal: a case study of computational journalism

The Guardian reportage of the United Kingdom Member of Parliament (MP) expenses scandal of 2009 used crowdsourcing and computational journalism techniques. Computational journalism can be broadly defined as the application of computer science techniques to the activities of journalism. Its foundation lies in computer assisted reporting techniques and its importance is increasing due to the: (a) increasing availability of large scale government datasets for scrutiny; (b) declining cost, increasing power and ease of use of data mining and filtering software; and Web 2.0; and (c) explosion of online public engagement and opinion.. This paper provides a case study of the Guardian MP expenses scandal reportage and reveals some key challenges and opportunities for digital journalism. It finds journalists may increasingly take an active role in understanding, interpreting, verifying and reporting clues or conclusions that arise from the interrogations of datasets (computational journalism). Secondly a distinction should be made between information reportage and computational journalism in the digital realm, just as a distinction might be made between citizen reporting and citizen journalism. Thirdly, an opportunity exists for online news providers to take a ‘curatorial’ role, selecting and making easily available the best data sources for readers to use (information reportage). These activities have always been fundamental to journalism, however the way in which they are undertaken may change. Findings from this paper may suggest opportunities and challenges for the implementation of computational journalism techniques in practice by digital Australian media providers, and further areas of research.

Using economic data to reduce healthcare-acquired infection

In this issue Burns et al. report an estimate of the economic loss to Auckland City Hospital from cases of healthcare-associated bloodstream infection. They show that patients with infection stay longer in hospital and this must impose an opportunity cost because beds are blocked. Harder to measure costs fall on patients, their families and non-acute health services. Patients face some risk of dying from the infection.

Interaction, privacy and profiling considerations in local mobile social software : a prototype agile ride share system

Agile ridesharing aims to utilise the capability of social networks and mobile phones to facilitate people to share vehicles and travel in real time. However the application of social networking technologies in local communities to address issues of personal transport faces significant design challenges. In this paper we describe an iterative design-based approach to exploring this problem and discuss findings from the use of an early prototype. The findings focus upon interaction, privacy and profiling. Our early results suggest that explicitly entering information such as ride data and personal profile data into formal fields for explicit computation of matches, as is done in many systems, may not be the best strategy. It might be preferable to support informal communication and negotiation with text search techniques.

An intelligent data mining technique for product quality improvement

Advances in data mining have provided techniques for automatically discovering underlying knowledge and extracting useful information from large volumes of data. Data mining offers tools for quick discovery of relationships, patterns and knowledge in large complex databases. Application of data mining to manufacturing is relatively limited mainly because of complexity of manufacturing data. Growing self organizing map (GSOM) algorithm has been proven to be an efficient algorithm to analyze unsupervised DNA data. However, it produced unsatisfactory clustering when used on some large manufacturing data. In this paper a data mining methodology has been proposed using a GSOM tool which was developed using a modified GSOM algorithm. The proposed method is used to generate clusters for good and faulty products from a manufacturing dataset. The clustering quality (CQ) measure proposed in the paper is used to evaluate the performance of the cluster maps. The paper also proposed an automatic identification of variables to find the most probable causative factor(s) that discriminate between good and faulty product by quickly examining the historical manufacturing data. The proposed method offers the manufacturers to smoothen the production flow and improve the quality of the products. Simulation results on small and large manufacturing data show the effectiveness of the proposed method.

Measuring falls events in acute hospitals-A comparison of three reporting methods to identify missing data in the hospital reporting system

OBJECTIVES: To compare three different methods of falls reporting and examine the characteristics of the data missing from the hospital incident reporting system. DESIGN: Fourteen-month prospective observational study nested within a randomized controlled trial. SETTING: Rehabilitation, stroke, medical, surgical, and orthopedic wards in Perth and Brisbane, Australia. PARTICIPANTS: Fallers (n5153) who were part of a larger trial (1,206 participants, mean age 75.1 � 11.0). MEASUREMENTS: Three falls events reporting measures: participants’ self-report of fall events, fall events reported in participants’ case notes, and falls events reported through the hospital reporting systems. RESULTS: The three reporting systems identified 245 falls events in total. Participants’ case notes captured 226 (92.2%) falls events, hospital incident reporting systems captured 185 (75.5%) falls events, and participant selfreport captured 147 (60.2%) falls events. Falls events were significantly less likely to be recorded in hospital reporting systems when a participant sustained a subsequent fall, (P5.01) or when the fall occurred in the morning shift (P5.01) or afternoon shift (P5.01). CONCLUSION: Falls data missing from hospital incident report systems are not missing completely at random and therefore will introduce bias in some analyses if the factor investigated is related to whether the data ismissing.Multimodal approaches to collecting falls data are preferable to relying on a single source alone.

Recognising audio-visual speech in vehicles using the AVICAR database

Interacting with technology within a vehicle environment using a voice interface can greatly reduce the effects of driver distraction. Most current approaches to this problem only utilise the audio signal, making them susceptible to acoustic noise. An obvious approach to circumvent this is to use the visual modality in addition. However, capturing, storing and distributing audio-visual data in a vehicle environment is very costly and difficult. One current dataset available for such research is the AVICAR [1] database. Unfortunately this database is largely unusable due to timing mismatch between the two streams and in addition, no protocol is available. We have overcome this problem by re-synchronising the streams on the phone-number portion of the dataset and established a protocol for further research. This paper presents the first audio-visual results on this dataset for speaker-independent speech recognition. We hope this will serve as a catalyst for future research in this area.

The role of informal networks in providing effective work opportunities for people with an intellectual disability

Being in paid employment is socially valued, and is linked to health, financial security and time use. Issues arising from a lack of occupational choice and control, and from diminished role partnerships are particularly problematic in the lives of people with an intellectual disability. Informal support networks are shown to influence work opportunities for people without disabilities, but their impact on the work experiences of people with disability has not been thoroughly explored. The experience of 'work' and preparation for work was explored with a group of four people with an intellectual disability (the participants) and the key members of their informal support networks (network members) in New South Wales, Australia. Network members and participants were interviewed and participant observations of work and other activities were undertaken. Data analysis included open, conceptual and thematic coding. Data analysis software assisted in managing the large datasets across multiple team members. The insight and actions of network members created and sustained the employment and support opportunities that effectively matched the needs and interests of the participants. Recommendations for future research are outlined.

Stronger difficulty notions for client puzzles and denial-of-service-resistant protocols

Client puzzles are meant to act as a defense against denial of service (DoS) attacks by requiring a client to solve some moderately hard problem before being granted access to a resource. However, recent client puzzle difficulty definitions (Stebila and Ustaoglu, 2009; Chen et al., 2009) do not ensure that solving n puzzles is n times harder than solving one puzzle. Motivated by examples of puzzles where this is the case, we present stronger definitions of difficulty for client puzzles that are meaningful in the context of adversaries with more computational power than required to solve a single puzzle. A protocol using strong client puzzles may still not be secure against DoS attacks if the puzzles are not used in a secure manner. We describe a security model for analyzing the DoS resistance of any protocol in the context of client puzzles and give a generic technique for combining any protocol with a strong client puzzle to obtain a DoS-resistant protocol.

A Data Picture of Australia's Arts and Entertainment Sector 2010

Australia’s Arts and Entertainment Sector underpins cultural and social innovation, improves the quality of community life, is essential to maintaining our cities as world class attractors of talent and investment, and helps create ‘Brand Australia’ in the global marketplace of ideas (QUT Creative Industries Faculty 2010). The sector makes a significant contribution to the Australian economy. So what is the size and nature of this contribution? The Creative Industries Faculty at Queensland University of Technology recently conducted an exercise to source and present statistics in order to produce a data picture of Australia’s Arts and Entertainment Sector. The exercise involved gathering the latest statistics on broadcasting, new media, performing arts, and music composition, distribution and publishing as well as Australia’s performance in world markets.

Using routinely collected hospital data for child maltreatment surveillance : issues, methods and patterns

Background: International data on child maltreatment are largely derived from child protection agencies, and predominantly report only substantiated cases of child maltreatment. This approach underestimates the incidence of maltreatment and makes inter-jurisdictional comparisons difficult. There has been a growing recognition of the importance of health professionals in identifying, documenting and reporting suspected child maltreatment. This study aimed to describe the issues around case identification using coded morbidity data, outline methods for selecting and grouping relevant codes, and illustrate patterns of maltreatment identified. Methods: A comprehensive review of the ICD-10-AM classification system was undertaken, including review of index terms, a free text search of tabular volumes, and a review of coding standards pertaining to child maltreatment coding. Identified codes were further categorised into maltreatment types including physical abuse, sexual abuse, emotional or psychological abuse, and neglect. Using these code groupings, one year of Australian hospitalisation data for children under 18 years of age was examined to quantify the proportion of patients identified and to explore the characteristics of cases assigned maltreatment-related codes. Results: Less than 0.5% of children hospitalised in Australia between 2005 and 2006 had a maltreatment code assigned, almost 4% of children with a principal diagnosis of a mental and behavioural disorder and over 1% of children with an injury or poisoning as the principal diagnosis had a maltreatment code assigned. The patterns of children assigned with definitive T74 codes varied by sex and age group. For males selected as having a maltreatment-related presentation, physical abuse was most commonly coded (62.6% of maltreatment cases) while for females selected as having a maltreatment-related presentation, sexual abuse was the most commonly assigned form of maltreatment (52.9% of maltreatment cases). Conclusion: This study has demonstrated that hospital data could provide valuable information for routine monitoring and surveillance of child maltreatment, even in the absence of population-based linked data sources. With national and international calls for a public health response to child maltreatment, better understanding of, investment in and utilisation of our core national routinely collected data sources will enhance the evidence-base needed to support an appropriate response to children at risk.

Reliability of routinely collected hospital data for child maltreatment surveillance

Background: Internationally, research on child maltreatment-related injuries has been hampered by a lack of available routinely collected health data to identify cases, examine causes, identify risk factors and explore health outcomes. Routinely collected hospital separation data coded using the International Classification of Diseases and Related Health Problems (ICD) system provide an internationally standardised data source for classifying and aggregating diseases, injuries, causes of injuries and related health conditions for statistical purposes. However, there has been limited research to examine the reliability of these data for child maltreatment surveillance purposes. This study examined the reliability of coding of child maltreatment in Queensland, Australia. Methods: A retrospective medical record review and recoding methodology was used to assess the reliability of coding of child maltreatment. A stratified sample of hospitals across Queensland was selected for this study, and a stratified random sample of cases was selected from within those hospitals. Results: In 3.6% of cases the coders disagreed on whether any maltreatment code could be assigned (definite or possible) versus no maltreatment being assigned (unintentional injury), giving a sensitivity of 0.982 and specificity of 0.948. The review of these cases where discrepancies existed revealed that all cases had some indications of risk documented in the records. 15.5% of cases originally assigned a definite or possible maltreatment code, were recoded to a more or less definite strata. In terms of the number and type of maltreatment codes assigned, the auditor assigned a greater number of maltreatment types based on the medical documentation than the original coder assigned (22% of the auditor coded cases had more than one maltreatment type assigned compared to only 6% of the original coded data). The maltreatment types which were the most ‘under-coded’ by the original coder were psychological abuse and neglect. Cases coded with a sexual abuse code showed the highest level of reliability. Conclusion: Given the increasing international attention being given to improving the uniformity of reporting of child-maltreatment related injuries and the emphasis on the better utilisation of routinely collected health data, this study provides an estimate of the reliability of maltreatment-specific ICD-10-AM codes assigned in an inpatient setting.

Getting research data ‘out there’ : collaborative solutions to identifying, describing and making research data more visible

At QUT research data refers to information that is generated or collected to be used as primary sources in the production of original research results, and which would be required to validate or replicate research findings (Callan, De Vine, & Baker, 2010). Making publicly funded research data discoverable by the broader research community and the public is a key aim of the Australian National Data Service (ANDS). Queensland University of Technology (QUT) has been innovating in this space by undertaking mutually dependant technical and content (metadata) focused projects funded by ANDS. Research Data Librarians identified and described datasets generated from Category 1 funded research at QUT, by interviewing researchers, collecting metadata and fashioning metadata records for upload to the Australian Research Data commons (ARDC) and exposure through the Research Data Australia interface. In parallel to this project, a Research Data Management Service and Metadata hub project were being undertaken by QUT High Performance Computing & Research Support specialists. These projects will collectively store and aggregate QUT’s metadata and research data from multiple repositories and administration systems and contribute metadata directly by OAI-PMH compliant feed to RDA. The pioneering nature of the work has resulted in a collaborative project dynamic where good data management practices and the discoverability and sharing of research data were the shared drivers for all activity. Each project’s development and progress was dependent on feedback from the other. The metadata structure evolved in tandem with the development of the repository and the development of the repository interface responded to meet the needs of the data interview process. The project environment was one of bottom-up collaborative approaches to process and system development which matched top-down strategic alliances crossing organisational boundaries in order to provide the deliverables required by ANDS. This paper showcases the work undertaken at QUT, focusing on the Seeding the Commons project as a case study, and illustrates how the data management projects are interconnected. It describes the processes and systems being established to make QUT research data more visible and the nature of the collaborations between organisational areas required to achieve this. The paper concludes with the Seeding the Commons project outcomes and the contribution this project made to getting more research data ‘out there’.

Enhancing security and continuity management at international airports

Operators of busy contemporary airports have to balance tensions between the timely flow of passengers, flight operations, the conduct of commercial business activities and the effective application of security processes. In addition to specific onsite issues airport operators liaise with a range of organisations which set and enforce aviation-related policies and regulations as well as border security agencies responsible for customs, quarantine and immigration, in addition to first response security services. The challenging demands of coordinating and planning in such complex socio-technical contexts place considerable pressure on airport management to facilitate coordination of what are often conflicting goals and expectations among groups that have standing in respect to safe and secure air travel. What are, as yet, significantly unexplored issues in large airports are options for the optimal coordination of efforts from the range of public and private sector participants active in airport security and crisis management. A further aspect of this issue is how airport management systems operate when there is a transition from business-as-usual into an emergency/crisis situation and then, on recovery, back to ‘normal’ functioning. Business Continuity Planning (BCP), incorporating sub-plans for emergency response, continuation of output and recovery of degraded operating capacity, would fit such a context. The implementation of BCP practices in such a significant high security setting offers considerable potential benefit yet entails considerable challenges. This paper presents early results of a 4 year nationally funded industry-based research project examining the merger of Business Continuity Planning and Transport Security Planning as a means of generating capability for improved security and reliability and, ultimately, enhanced resilience in major airports. The project is part of a larger research program on the Design of Secure Airports that includes most of the gazetted ‘first response’ international airports in Australia, key Aviation industry groups and all aviation-related border and security regulators as collaborative partners. The paper examines a number of initial themes in the research, including: ? Approaches to integrating Business Continuity & Aviation Security Planning within airport operations; ? Assessment of gaps in management protocols and operational capacities for identifying and responding to crises within and across critical aviation infrastructure; ? Identification of convergent and divergent approaches to crisis management used across Austral-Asia and their alignment to planned and possible infrastructure evolution.