Entertainment industries : entertainment as a cultural system

Entertainment Industries is the first book to map entertainment as a cultural system. Including work from world-renowned analysts such as Henry Jenkins and Jonathan Gray, this innovative collection explains what entertainment is and how it works. Entertainment is audience-centred culture. The Entertainment Industries are a uniquely interdisciplinary collection of evolving businesses that openly monitor evolving cultural trends and work within them. The producers of entertainment – central to that practice– are the new artists. They understand audiences and combine creative, business and legal skills in order to produce cultural products that cater to them. Entertainment Industries describes the characteristics of entertainment, the systems that produce it, and the role of producers and audiences in its development, as well as explaining the importance of this area of study, and how it might be better integrated into Universities.

An expressed sequence tag (EST) library for Drosophila serrata, a model system for sexual selection and climatic adaptation studies

The native Australian fly Drosophila serrata belongs to the highly speciose montium subgroup of the melanogaster species group. It has recently emerged as an excellent model system with which to address a number of important questions, including the evolution of traits under sexual selection and traits involved in climatic adaptation along latitudinal gradients. Understanding the molecular genetic basis of such traits has been limited by a lack of genomic resources for this species. Here, we present the first expressed sequence tag (EST) collection for D. serrata that will enable the identification of genes underlying sexually-selected phenotypes and physiological responses to environmental change and may help resolve controversial phylogenetic relationships within the montium subgroup.

Health complaint commissions in Australia : time for a national approach to data collection

Health complaint statistics are important for identifying problems and bringing about improvements to health care provided by health service providers and to the wider health care system. This paper overviews complaints handling by the eight Australian state and territory health complaint entities, based on an analysis of data from their annual reports. The analysis shows considerable variation between jurisdictions in the ways complaint data are defined, collected and recorded. Complaints from the public are an important accountability mechanism and open a window on service quality. The lack of a national approach leads to fragmentation of complaint data and a lost opportunity to use national data to assist policy development and identify the main areas causing consumers to complain. We need a national approach to complaints data collection in order to better respond to patients’ concerns.

Juveniles’ contact with the criminal justice system in Australia

This report presents the first collection of data on juveniles’ contact with the criminal justice system as both alleged/convicted offenders and complainants/victims in New South Wales, the Australian Capital Territory, Victoria, Queensland, Western Australia, South Australia and the Northern Territory. Its primary objectives are to outline data from each of these jurisdictions on juveniles’ contact with the policing, courts and correctional systems and to determine what we do and do not know about juveniles’ contact with the criminal justice system.

A critical assessment of the Australian OHS accreditation system's "Body of Knowledge (BoK)"

In response to an increasing perception of poor OHS consultancy quality amongst the Australian public, regulator and OHS professionals, the Safety Institute Australia (SIA) was tasked by the Victorian government to establish an accreditation process for OHS professionals. The OHS accreditation board decided to base its accreditation on a core "body of knowledge" (BoK), against which applicants are assesssed. While the foundation and structure of the BoK is unclear, the BoK consists of a collection of essays from a variety of invited authors. The BoK comprises about 811 pages in 34 chapters, with significant redundancy and considerable subjective components. The SIA BoK is benchmarked against two international best-practices, the German "Core Definition, Object Catalog and Research Domains of Labour Science (Ergonomics)" (Luzcak, Volpert, Raeithel & Schwier, 1989)(100 pages) and the American "Core Competency Model" for the "Master's Degree in Public Health" (Association of Schools of Public Health, 2006) (21 pages). Both "core definition" and "core competency model" are on a comparative level to the BoK. While the German expert panel consisted of 14 eminent professors, the American panel consisted of 135 members, organized in 6 groups chaired by discipline leading academics. The Australian approach employed a broad approach, where 137 professionals, consultants, emerging academics and academics contributed to 8 workshops. Both the German and the American panels maintained an open communication amongst members and with the discipline community throughout the process, whereas SIA applied an open and directed peer-review process. Moreover, the German process involved an analysis of all congress content and journal publications in the scientific domain in a set timeframe, which were then systematically clustered. These results were further expanded by structured interviews with 38 professors in the discpline, grasping their research and teaching practice. The American workgroup however assumed core scientific areas, underlying the domain. Based upon the a-priori assumption, they then established well defined competencies across all areas using a modified Delphi process. Although the BoK attempts to explore the knowledge in the OHS domain without an imposed structure in a bottom-up approach, it does not result in a structured systematic of the science. We conclude that the outcome of the German, rigorous academic approach, and the US American democratic approach under unambiguous academic leadership both outperform the Australian advocacy group approach. This product was determined for both structure and content of the taxonomy delivered through the processes.

Factors associated with the isolation of Nontuberculous mycobacteria (NTM) from a large municipal water system in Brisbane, Australia

Background Nontuberculous mycobacteria (NTM) are normal inhabitants of a variety of environmental reservoirs including natural and municipal water. The aim of this study was to document the variety of species of NTM in potable water in Brisbane, QLD, with a specific interest in the main pathogens responsible for disease in this region and to explore factors associated with the isolation of NTM. One-litre water samples were collected from 189 routine collection sites in summer and 195 sites in winter. Samples were split, with half decontaminated with CPC 0.005%, then concentrated by filtration and cultured on 7H11 plates in MGIT tubes (winter only). Results Mycobacteria were grown from 40.21% sites in Summer (76/189) and 82.05% sites in winter (160/195). The winter samples yielded the greatest number and variety of mycobacteria as there was a high degree of subculture overgrowth and contamination in summer. Of those samples that did yield mycobacteria in summer, the variety of species differed from those isolated in winter. The inclusion of liquid media increased the yield for some species of NTM. Species that have been documented to cause disease in humans residing in Brisbane that were also found in water include M. gordonae, M. kansasii, M. abscessus, M. chelonae, M. fortuitum complex, M. intracellulare, M. avium complex, M. flavescens, M. interjectum, M. lentiflavum, M. mucogenicum, M. simiae, M. szulgai, M. terrae. M. kansasii was frequently isolated, but M. avium and M. intracellulare (the main pathogens responsible for disease is QLD) were isolated infrequently. Distance of sampling site from treatment plant in summer was associated with isolation of NTM. Pathogenic NTM (defined as those known to cause disease in QLD) were more likely to be identified from sites with narrower diameter pipes, predominantly distribution sample points, and from sites with asbestos cement or modified PVC pipes. Conclusions NTM responsible for human disease can be found in large urban water distribution systems in Australia. Based on our findings, additional point chlorination, maintenance of more constant pressure gradients in the system, and the utilisation of particular pipe materials should be considered.

Enterprise system lifecycle-wide innovation - research in progress

Enterprise Systems purport to bring innovation to organizations. Yet, no past studies, neither from innovation nor from ES disciplines have merged their knowledge to understand how ES could facilitate lifecycle-wide innovation. Therefore, this study forms conceptual bridge between the two disciplines. In this research, we seek to understand how ES could facilitate innovation across its lifecycle phases. We associate classifications of innovation such as radical vs. incremental, administrative vs. technical innovation with the three phases of ES lifecycle. We introduce Continuous Restrained Innovation (CRI) as a new type of innovation specific to ES, considering restraints of technology, business processes and organization. Our empirical data collection at the implementation phase, using data from both the client and implementation partner, shows preliminary evidence of CRI. In addition, we state that both parties consider the implementation of ES as a radical innovation yet, are less interest in seeking further innovations through the system.

Understanding and analyzing a large collection of archived swimming videos

In elite sports, nearly all performances are captured on video. Despite the massive amounts of video that has been captured in this domain over the last 10-15 years, most of it remains in an 'unstructured' or 'raw' form, meaning it can only be viewed or manually annotated/tagged with higher-level event labels which is time consuming and subjective. As such, depending on the detail or depth of annotation, the value of the collected repositories of archived data is minimal as it does not lend itself to large-scale analysis and retrieval. One such example is swimming, where each race of a swimmer is captured on a camcorder and in-addition to the split-times (i.e., the time it takes for each lap), stroke rate and stroke-lengths are manually annotated. In this paper, we propose a vision-based system which effectively 'digitizes' a large collection of archived swimming races by estimating the location of the swimmer in each frame, as well as detecting the stroke rate. As the videos are captured from moving hand-held cameras which are located at different positions and angles, we show our hierarchical-based approach to tracking the swimmer and their different parts is robust to these issues and allows us to accurately estimate the swimmer location and stroke rates.

Mathematical Models of Tumor-Immune System Dynamics

"This collection of papers offers a broad synopsis of state-of-the-art mathematical methods used in modeling the interaction between tumors and the immune system. These papers were presented at the four-day workshop on Mathematical Models of Tumor-Immune System Dynamics held in Sydney, Australia from January 7th to January 10th, 2013. The workshop brought together applied mathematicians, biologists, and clinicians actively working in the field of cancer immunology to share their current research and to increase awareness of the innovative mathematical tools that are applicable to the growing field of cancer immunology. Recent progress in cancer immunology and advances in immunotherapy suggest that the immune system plays a fundamental role in host defense against tumors and could be utilized to prevent or cure cancer. Although theoretical and experimental studies of tumor-immune system dynamics have a long history, there are still many unanswered questions about the mechanisms that govern the interaction between the immune system and a growing tumor. The multidimensional nature of these complex interactions requires a cross-disciplinary approach to capture more realistic dynamics of the essential biology. The papers presented in this volume explore these issues and the results will be of interest to graduate students and researchers in a variety of fields within mathematical and biological sciences."--Publisher website

A tag-based personalized item recommendation system using tensor modeling and topic model approaches

This research falls in the area of enhancing the quality of tag-based item recommendation systems. It aims to achieve this by employing a multi-dimensional user profile approach and by analyzing the semantic aspects of tags. Tag-based recommender systems have two characteristics that need to be carefully studied in order to build a reliable system. Firstly, the multi-dimensional correlation, called as tag assignment , should be appropriately modelled in order to create the user profiles [1]. Secondly, the semantics behind the tags should be considered properly as the flexibility with their design can cause semantic problems such as synonymy and polysemy [2]. This research proposes to address these two challenges for building a tag-based item recommendation system by employing tensor modeling as the multi-dimensional user profile approach, and the topic model as the semantic analysis approach. The first objective is to optimize the tensor model reconstruction and to improve the model performance in generating quality rec-ommendation. A novel Tensor-based Recommendation using Probabilistic Ranking (TRPR) method [3] has been developed. Results show this method to be scalable for large datasets and outperforming the benchmarking methods in terms of accuracy. The memory efficient loop implements the n-mode block-striped (matrix) product for tensor reconstruction as an approximation of the initial tensor. The probabilistic ranking calculates the probabil-ity of users to select candidate items using their tag preference list based on the entries generated from the reconstructed tensor. The second objective is to analyse the tag semantics and utilize the outcome in building the tensor model. This research proposes to investigate the problem using topic model approach to keep the tags nature as the “social vocabulary” [4]. For the tag assignment data, topics can be generated from the occurrences of tags given for an item. However there is only limited amount of tags availa-ble to represent items as collection of topics, since an item might have only been tagged by using several tags. Consequently, the generated topics might not able to represent the items appropriately. Furthermore, given that each tag can belong to any topics with various probability scores, the occurrence of tags cannot simply be mapped by the topics to build the tensor model. A standard weighting technique will not appropriately calculate the value of tagging activity since it will define the context of an item using a tag instead of a topic.

Pollen image classification using the classifynder system: Algorithm comparison and a case study on New Zealand honey

We describe an investigation into how Massey University’s Pollen Classifynder can accelerate the understanding of pollen and its role in nature. The Classifynder is an imaging microscopy system that can locate, image and classify slide based pollen samples. Given the laboriousness of purely manual image acquisition and identification it is vital to exploit assistive technologies like the Classifynder to enable acquisition and analysis of pollen samples. It is also vital that we understand the strengths and limitations of automated systems so that they can be used (and improved) to compliment the strengths and weaknesses of human analysts to the greatest extent possible. This article reviews some of our experiences with the Classifynder system and our exploration of alternative classifier models to enhance both accuracy and interpretability. Our experiments in the pollen analysis problem domain have been based on samples from the Australian National University’s pollen reference collection (2,890 grains, 15 species) and images bundled with the Classifynder system (400 grains, 4 species). These samples have been represented using the Classifynder image feature set.We additionally work through a real world case study where we assess the ability of the system to determine the pollen make-up of samples of New Zealand honey. In addition to the Classifynder’s native neural network classifier, we have evaluated linear discriminant, support vector machine, decision tree and random forest classifiers on these data with encouraging results. Our hope is that our findings will help enhance the performance of future releases of the Classifynder and other systems for accelerating the acquisition and analysis of pollen samples.

A comparison of classification algorithms within the Classifynder pollen imaging system

We describe an investigation into how Massey University's Pollen Classifynder can accelerate the understanding of pollen and its role in nature. The Classifynder is an imaging microscopy system that can locate, image and classify slide based pollen samples. Given the laboriousness of purely manual image acquisition and identification it is vital to exploit assistive technologies like the Classifynder to enable acquisition and analysis of pollen samples. It is also vital that we understand the strengths and limitations of automated systems so that they can be used (and improved) to compliment the strengths and weaknesses of human analysts to the greatest extent possible. This article reviews some of our experiences with the Classifynder system and our exploration of alternative classifier models to enhance both accuracy and interpretability. Our experiments in the pollen analysis problem domain have been based on samples from the Australian National University's pollen reference collection (2890 grains, 15 species) and images bundled with the Classifynder system (400 grains, 4 species). These samples have been represented using the Classifynder image feature set. In addition to the Classifynder's native neural network classifier, we have evaluated linear discriminant, support vector machine, decision tree and random forest classifiers on these data with encouraging results. Our hope is that our findings will help enhance the performance of future releases of the Classifynder and other systems for accelerating the acquisition and analysis of pollen samples. © 2013 AIP Publishing LLC.

Towards coordinated multirobot missions for lunar sample collection in an unknown environment

In this paper, the recent results of the space project IMPERA are presented. The goal of IMPERA is the development of a multirobot planning and plan execution architecture with a focus on a lunar sample collection scenario in an unknown environment. We describe the implementation and verification of different modules that are integrated into a distributed system architecture. The modules include a mission planning approach for a multirobot system and modules for task and skill execution within a lunar use-case scenario. The skills needed for the test scenario include cooperative exploration and mapping strategies for an unknown environment, the localization and classification of sample containers using a novel approach of semantic perception, and the skill of transporting sample containers to a collection point using a mobile manipulation robot. Additionally, we present our approach of a reliable communication framework that can deal with communication loss during the mission. Several modules are tested within several experiments in the domain of planning and plan execution, communication, coordinated exploration, perception, and object transportation. An overall system integration is tested on a mission scenario experiment using three robots.

Towards the development of a low cost airborne sensing system to monitor dust particles after blasting at open-pit mine sites

Blasting is an integral part of large-scale open cut mining that often occurs in close proximity to population centers and often results in the emission of particulate material and gases potentially hazardous to health. Current air quality monitoring methods rely on limited numbers of fixed sampling locations to validate a complex fluid environment and collect sufficient data to confirm model effectiveness. This paper describes the development of a methodology to address the need of a more precise approach that is capable of characterizing blasting plumes in near-real time. The integration of the system required the modification and integration of an opto-electrical dust sensor, SHARP GP2Y10, into a small fixed-wing and multi-rotor copter, resulting in the collection of data streamed during flight. The paper also describes the calibration of the optical sensor with an industry grade dust-monitoring device, Dusttrak 8520, demonstrating a high correlation between them, with correlation coefficients (R2) greater than 0.9. The laboratory and field tests demonstrate the feasibility of coupling the sensor with the UAVs. However, further work must be done in the areas of sensor selection and calibration as well as flight planning.

Organisational driving safety systems analysis: Fleet safety situational issues and system gaps

The identification of safety hazards and risks and their associated control measures provides the foundation for any safety program and essentially determines the scope, content and complexity of an effective occupational health and safety management system. In the case of work-related road safety (WRRS), there is a gap within current knowledge, research and practice regarding the holistic assessment of WRRS safety systems and practice. In order to mitigate this gap, a multi-level process tool for assessing WRRS safety systems was developed from extensive consultation, practice and informed by theoretical models and frameworks. Data collection for the Organisational Driving Safety Systems Analysis (ODSSA) tool utilised a case study methodology and included multiple information sources: such as documents, archival records, interviews, direct observations, participant observations, and physical artefacts. Previous trials and application of the ODSSA has indicated that the tool is applicable to a wide range of organisational fleet environments and settings. This paper reports on the research results and effectiveness of the ODSSA tool to assess WRRS systems across a large organisation that recently underwent considerable organisational change, including amalgamation of multiple organisations. The outcomes of this project identified considerable differences in the degree by which the organisation addressed WRRS across their vehicle fleet operations and provided guidelines for improving organisations’ WRRS systems. The ODSSA tool was pivotal in determining WRRS system deficiencies and provided a platform to inform mitigation and improvement strategies.