Predicting shot locations in tennis using spatiotemporal data

Over the past decade, vision-based tracking systems have been successfully deployed in professional sports such as tennis and cricket for enhanced broadcast visualizations as well as aiding umpiring decisions. Despite the high-level of accuracy of the tracking systems and the sheer volume of spatiotemporal data they generate, the use of this high quality data for quantitative player performance and prediction has been lacking. In this paper, we present a method which predicts the location of a future shot based on the spatiotemporal parameters of the incoming shots (i.e. shot speed, location, angle and feet location) from such a vision system. Having the ability to accurately predict future short-term events has enormous implications in the area of automatic sports broadcasting in addition to coaching and commentary domains. Using Hawk-Eye data from the 2012 Australian Open Men's draw, we utilize a Dynamic Bayesian Network to model player behaviors and use an online model adaptation method to match the player's behavior to enhance shot predictability. To show the utility of our approach, we analyze the shot predictability of the top 3 players seeds in the tournament (Djokovic, Federer and Nadal) as they played the most amounts of games.

Automatic de-identification of electronic health records : an Australian perspective

We present an approach to automatically de-identify health records. In our approach, personal health information is identified using a Conditional Random Fields machine learning classifier, a large set of linguistic and lexical features, and pattern matching techniques. Identified personal information is then removed from the reports. The de-identification of personal health information is fundamental for the sharing and secondary use of electronic health records, for example for data mining and disease monitoring. The effectiveness of our approach is first evaluated on the 2007 i2b2 Shared Task dataset, a widely adopted dataset for evaluating de-identification techniques. Subsequently, we investigate the robustness of the approach to limited training data; we study its effectiveness on different type and quality of data by evaluating the approach on scanned pathology reports from an Australian institution. This data contains optical character recognition errors, as well as linguistic conventions that differ from those contained in the i2b2 dataset, for example different date formats. The findings suggest that our approach compares to the best approach from the 2007 i2b2 Shared Task; in addition, the approach is found to be robust to variations of training size, data type and quality in presence of sufficient training data.

The importance of accurate beam data measurement for SRT/SRS treatment planning

Introduction This study investigated the sensitivity of calculated stereotactic radiotherapy and radiosurgery doses to the accuracy of the beam data used by the treatment planning system. Methods Two sets of field output factors were acquired using fields smaller than approximately 1 cm2, for inclusion in beam data used by the iPlan treatment planning system (Brainlab, Feldkirchen, Germany). One set of output factors were measured using an Exradin A16 ion chamber (Standard Imaging, Middleton, USA). Although this chamber has a relatively small collecting volume (0.007 cm3), measurements made in small fields using this chamber are subject to the effects of volume averaging, electronic disequilibrium and chamber perturbations. The second, more accurate, set of measurements were obtained by applying perturbation correction factors, calculated using Monte Carlo simulations according to a method recommended by Cranmer-Sargison et al. [1] to measurements made using a 60017 unshielded electron diode (PTW, Freiburg, Germany). A series of 12 sample patient treatments were used to investigate the effects of beam data accuracy on resulting planned dose. These treatments, which involved 135 fields, were planned for delivery via static conformal arcs and 3DCRT techniques, to targets ranging from prostates (up to 8 cm across) to meningiomas (usually more than 2 cm across) to arterioveinous malformations, acoustic neuromas and brain metastases (often less than 2 cm across). Isocentre doses were calculated for all of these fields using iPlan, and the results of using the two different sets of beam data were evaluated. Results While the isocentre doses for many fields are identical (difference = 0.0 %), there is a general trend for the doses calculated using the data obtained from corrected diode measurements to exceed the doses calculated using the less-accurate Exradin ion chamber measurements (difference\0.0 %). There are several alarming outliers (circled in the Fig. 1) where doses differ by more than 3 %, in beams from sample treatments planned for volumes up to 2 cm across. Discussion and conclusions These results demonstrate that treatment planning dose calculations for SRT/SRS treatments can be substantially affected when beam data for fields smaller than approximately 1 cm2 are measured inaccurately, even when treatment volumes are up to 2 cm across.

CTCombine : rotating and combining CT data with an accurate detector model to simulate radiotherapy portal imaging at non-zero beam angles

Established Monte Carlo user codes BEAMnrc and DOSXYZnrc permit the accurate and straightforward simulation of radiotherapy experiments and treatments delivered from multiple beam angles. However, when an electronic portal imaging detector (EPID) is included in these simulations, treatment delivery from non-zero beam angles becomes problematic. This study introduces CTCombine, a purpose-built code for rotating selected CT data volumes, converting CT numbers to mass densities, combining the results with model EPIDs and writing output in a form which can easily be read and used by the dose calculation code DOSXYZnrc...

Adherence to physical activity and electronic media guidelines in Australian pre-school children

The aim of this study was to determine compliance with the National Association for Sport and Physical Education (NASPE) guideline for physical activity and American Academy of Pediatrics (AAP) recommendation for electronic media use among urban pre-school children in two large cities on the East Coast of Australia. Cross-sectional data were collected from 266 parents. Time spent using electronic media (watching television, DVDs or on the computer) and in physical activity were parent reported. The proportion who met each guideline was calculated. 56 per cent and 79% of children met the NASPE guideline on weekdays and weekends, respectively, while 73% and 70% met the AAP recommendation on weekdays and weekends, with no difference between boys and girls. A substantial minority do not meet physical activity and electronic media use recommendations, highlighting the need to better understand what factors contribute to physical activity and electronic media use among this group of pre-schoolers.

eHealth-as-a-Service (eHaaS) : a data-driven decision making approach in Australian context

A commitment in 2010 by the Australian Federal Government to spend $466.7 million dollars on the implementation of personally controlled electronic health records (PCEHR) heralded a shift to a more effective and safer patient centric eHealth system. However, deployment of the PCEHR has met with much criticism, emphasised by poor adoption rates over the first 12 months of operation. An indifferent response by the public and healthcare providers largely sceptical of its utility and safety speaks to the complex sociotechnical drivers and obstacles inherent in the embedding of large (national) scale eHealth projects. With government efforts to inflate consumer and practitioner engagement numbers giving rise to further consumer disillusionment, broader utilitarian opportunities available with the PCEHR are at risk. This paper discusses the implications of establishing the PCEHR as the cornerstone of a holistic eHealth strategy for the aggregation of longitudinal patient information. A viewpoint is offered that the real value in patient data lies not just in the collection of data but in the integration of this information into clinical processes within the framework of a commoditised data-driven approach. Consideration is given to the eHealth-as-a-Service (eHaaS) construct as a disruptive next step for co-ordinated individualised healthcare in the Australian context.

Structural, electronic, and optical properties of wurtzite and rocksalt InN under pressure

Structural stability, electronic, and optical properties of InN under high pressure are studied using the first-principles calculations. The lattice constants and electronic band structure are found consistent with the available experimental and theoretical values. The pressure of the wurtzite-to-rocksalt structural transition is 13.4 GPa, which is in an excellent agreement with the most recent experimental values. The optical characteristics reproduce the experimental data thus justifying the feasibility of our theoretical predictions of the optical properties of InN at high pressures.

Machine learning approaches to analysing textual injury surveillance data: A systematic review

Objective To synthesise recent research on the use of machine learning approaches to mining textual injury surveillance data. Design Systematic review. Data sources The electronic databases which were searched included PubMed, Cinahl, Medline, Google Scholar, and Proquest. The bibliography of all relevant articles was examined and associated articles were identified using a snowballing technique. Selection criteria For inclusion, articles were required to meet the following criteria: (a) used a health-related database, (b) focused on injury-related cases, AND used machine learning approaches to analyse textual data. Methods The papers identified through the search were screened resulting in 16 papers selected for review. Articles were reviewed to describe the databases and methodology used, the strength and limitations of different techniques, and quality assurance approaches used. Due to heterogeneity between studies meta-analysis was not performed. Results Occupational injuries were the focus of half of the machine learning studies and the most common methods described were Bayesian probability or Bayesian network based methods to either predict injury categories or extract common injury scenarios. Models were evaluated through either comparison with gold standard data or content expert evaluation or statistical measures of quality. Machine learning was found to provide high precision and accuracy when predicting a small number of categories, was valuable for visualisation of injury patterns and prediction of future outcomes. However, difficulties related to generalizability, source data quality, complexity of models and integration of content and technical knowledge were discussed. Conclusions The use of narrative text for injury surveillance has grown in popularity, complexity and quality over recent years. With advances in data mining techniques, increased capacity for analysis of large databases, and involvement of computer scientists in the injury prevention field, along with more comprehensive use and description of quality assurance methods in text mining approaches, it is likely that we will see a continued growth and advancement in knowledge of text mining in the injury field.

Data driven and practice-based evidence : design and development of efficient and effective clinical decision support system

Decision-making is such an integral aspect in health care routine that the ability to make the right decisions at crucial moments can lead to patient health improvements. Evidence-based practice, the paradigm used to make those informed decisions, relies on the use of current best evidence from systematic research such as randomized controlled trials. Limitations of the outcomes from randomized controlled trials (RCT), such as “quantity” and “quality” of evidence generated, has lowered healthcare professionals’ confidence in using EBP. An alternate paradigm of Practice-Based Evidence has evolved with the key being evidence drawn from practice settings. Through the use of health information technology, electronic health records (EHR) capture relevant clinical practice “evidence”. A data-driven approach is proposed to capitalize on the benefits of EHR. The issues of data privacy, security and integrity are diminished by an information accountability concept. Data warehouse architecture completes the data-driven approach by integrating health data from multi-source systems, unique within the healthcare environment.

The Global Protection of Personal Health Data

The workshop is an activity of the IMIA Working Group ‘Security in Health Information Systems’ (SiHIS). It is focused to the growing global problem: how to protect personal health data in today’s global eHealth and digital health environment. It will review available trust building mechanisms, security measures and privacy policies. Technology alone does not solve this complex problem and current protection policies and legislation are considered woefully inadequate. Among other trust building tools, certification and accreditation mechanisms are dis-cussed in detail and the workshop will determine their acceptance and quality. The need for further research and international collective action are discussed. This workshop provides an opportunity to address a critical growing problem and make pragmatic proposals for sustainable and effective solutions for global eHealth and digital health.

Focusing on what counts: Using exploratory focus groups to enhance the development of an electronic survey in a mixed-methods research design

This paper describes the use of exploratory focus groups to inform the development of a survey instrument in a sequential phase mixed methods study investigating differences in secondary students’ career choice capability. Five focus groups were conducted with 23 year 10 students in the state of New South Wales (NSW), Australia. Analysis of the focus group data informed the design of the instrument for the second phase of the research project: a large-scale cross-sectional survey. In this paper, we discuss the benefits of using sequential phase mixed method approaches when inquiring into complex phenomena such as human capability.

Straightforward data management at QUT

QUT Library Research Support has simplified and streamlined the process of research data management planning, storage, discovery and reuse through collaboration and the use of integrated and tailored online tools, and a simplification of the metadata schema. This poster presents the integrated data management services a QUT, including QUT’s Data Management Planning Tool, Research Data Finder, Spatial Data Finder and Software Finder, and information on the simplified Registry Interchange Format – Collections and Services (RIF-CS) Schema. The QUT Data Management Planning (DMP) Tool was built using the Digital Curation Centre’s DMP Online Tool and modified to QUT’s needs and policies. The tool allows researchers and Higher Degree Research students to plan how to handle research data throughout the active phase of their research. The plan is promoted as a ‘live’ document’ and researchers are encouraged to update it as required. The information entered into the plan can be made private or shared with supervisors, project members and external examiners. A plan is mandatory when requesting storage space on the QUT Research Data Storage Service. QUT’s Research Data Finder is integrated with QUT’s Academic Profiles and the Data Management Planning Tool to create a seamless data management process. This process aims to encourage the creation of high quality rich records which facilitate discovery and reuse of quality data. The Registry Interchange Format – Collections and Services (RIF-CS) Schema that is used in the QUT Research Data Finder was simplified to “RIF-CS lite” to reflect mandatory and optional metadata requirements. RIF-CS lite removed schema fields that were underused or extra to the needs of the users and system. This has reduced the amount of metadata fields required from users and made integration of systems a far more simple process where field content is easily shared across services making the process of collecting metadata as transparent as possible.

Improving PLDA speaker verification using WMFD and linear-weighted approaches in limited microphone data conditions

This paper proposes the addition of a weighted median Fisher discriminator (WMFD) projection prior to length-normalised Gaussian probabilistic linear discriminant analysis (GPLDA) modelling in order to compensate the additional session variation. In limited microphone data conditions, a linear-weighted approach is introduced to increase the influence of microphone speech dataset. The linear-weighted WMFD-projected GPLDA system shows improvements in EER and DCF values over the pooled LDA- and WMFD-projected GPLDA systems in inter-view-interview condition as WMFD projection extracts more speaker discriminant information with limited number of sessions/ speaker data, and linear-weighted GPLDA approach estimates reliable model parameters with limited microphone data.

Electronic games: Can they create value for the moderate drinking brand?

Purpose This paper aims to understand how experiential value can generate awareness, image, perceived quality and loyalty to the moderate drinking brand. Electronic games are increasingly used by social marketers in an attempt to support target audiences uptake of social behaviours. However, little is known of the value this creates for target audiences and its impact on the uptake of a social behaviour brand. Design/methodology/approach A survey of male adolescents (n = 137) was conducted to test proposed relationships between experiential value and consumer-based brand equity dimensions. The research tested the game “Don’t Turn a Night Out into a Nightmare” that was developed by the Australian Federal Government as part of a social marketing campaign. Data were analysed using linear regression and MANCOVA. Findings The findings indicate that there are significant relationships between consumer-based brand equity dimensions for the social behaviour brand of moderate drinking, indicating relevance of a commercial marketing theory for social marketing. Furthermore, findings show that different combinations of experiential value dimensions have an impact on different components of consumer-based brand equity. These findings indicate that when social marketers are developing electronic games, they must create different combinations of value in game play to achieve awareness, positive image, high perceived quality and, ultimately, loyalty to a behaviour. Practical implications Social marketers seeking to use electronic games to influence the uptake of behaviour brands such as moderate drinking must provide a more complete value package. Originality/value This paper is the first to examine how experiential value can influence the creation of brand equity for a social behaviour brand.

Paper and electronic antenatal records: What do women and health care providers tell us about their use?

The antenatal paper hand-held record (PHR) has been used extensively in general practice (GP) shared-care management of pregnant women, but recently the antenatal electronic health record (EHR) was introduced. This study aimed to examine the experiences of women and health care providers who use the PHR and the EHR, and find out the relative role of these records in the integration of care. Purposive homogenous samples of women and health care providers were interviewed as users of the PHR in phase 1 and the EHR in phase 2 of the study. Qualitative data were collected via interview with women and GPs and focus groups held with hospital health care providers. Interviews were coded manually and analysed using qualitative content analysis. Fifteen women participated in phase 1 and 12 in phase 2. Seventeen GPs participated in phase 1 and 15 in phase 2. Five focus groups with hospital health care providers were conducted in each phase. Results were categorised into four themes: 1. Record purpose; 2. Perception of the record; 3. Content of the record, and; 4. Sharing information in the record. Both women and health care providers were familiar with the PHR, but identified that some information was missing or not utilised well, and reported underuse of the EHR. The study identified continued widespread use of the PHR and several issues concerning the use of the EHR. An improvement in the strategic implementation of the EHR is suggested as a mechanism to facilitate its wider adoption.