From science to management : using Bayesian networks to learn about Lyngbya

Toxic blooms of Lyngbya majuscula occur in coastal areas worldwide and have major ecological, health and economic consequences. The exact causes and combinations of factors which lead to these blooms are not clearly understood. Lyngbya experts and stakeholders are a particularly diverse group, including ecologists, scientists, state and local government representatives, community organisations, catchment industry groups and local fishermen. An integrated Bayesian Network approach was developed to better understand and model this complex environmental problem, identify knowledge gaps, prioritise future research and evaluate management options.

Tangled Webs : Using Bayesian Networks in the Fight Against Infection

Bayesian networks (BNs) provide a statistical modelling framework which is ideally suited for modelling the many factors and components of complex problems such as healthcare-acquired infections. The methicillin-resistant Staphylococcus aureus (MRSA) organism is particularly troublesome since it is resistant to standard treatments for Staph infections. Overcrowding and understa�ng are believed to increase infection transmission rates and also to inhibit the effectiveness of disease control measures. Clearly the mechanisms behind MRSA transmission and containment are very complicated and control strategies may only be e�ective when used in combination. BNs are growing in popularity in general and in medical sciences in particular. A recent Current Content search of the number of published BN journal articles showed a fi�ve fold increase in general and a six fold increase in medical and veterinary science from 2000 to 2009. This chapter introduces the reader to Bayesian network (BN) modelling and an iterative modelling approach to build and test the BN created to investigate the possible role of high bed occupancy on transmission of MRSA while simultaneously taking into account other risk factors.

The multi-platform user engagement and data visualisation tool

The ability to identify and assess user engagement with transmedia productions is vital to the success of individual projects and the sustainability of this mode of media production as a whole. It is essential that industry players have access to tools and methodologies that offer the most complete and accurate picture of how audiences/users engage with their productions and which assets generate the most valuable returns of investment. Drawing upon research conducted with Hoodlum Entertainment, a Brisbane-based transmedia producer, this project involved an initial assessment of the way engagement tends to be understood, why standard web analytics tools are ill-suited to measuring it, how a customised tool could offer solutions, and why this question of measuring engagement is so vital to the future of transmedia as a sustainable industry. Working with data provided by Hoodlum Entertainment and Foxtel Marketing, the outcome of the study was a prototype for a custom data visualisation tool that allowed access, manipulation and presentation of user engagement data, both historic and predictive. The prototyped interfaces demonstrate how the visualization tool would collect and organise data specific to multiplatform projects by aggregating data across a number of platform reporting tools. Such a tool is designed to encompass not only platforms developed by the transmedia producer but also sites developed by fans. This visualisation tool accounted for multiplatform experience projects whose top level is comprised of people, platforms and content. People include characters, actors, audience, distributors and creators. Platforms include television, Facebook and other relevant social networks, literature, cinema and other media that might be included in the multiplatform experience. Content refers to discreet media texts employed within the platform, such as tweet, a You Tube video, a Facebook post, an email, a television episode, etc. Core content is produced by the creators’ multiplatform experiences to advance the narrative, while complimentary content generated by audience members offers further contributions to the experience. Equally important is the timing with which the components of the experience are introduced and how they interact with and impact upon each other. Being able to combine, filter and sort these elements in multiple ways we can better understand the value of certain components of a project. It also offers insights into the relationship between the timing of the release of components and user activity associated with them, which further highlights the efficacy (or, indeed, failure) of assets as catalysts for engagement. In collaboration with Hoodlum we have developed a number of design scenarios experimenting with the ways in which data can be visualised and manipulated to tell a more refined story about the value of user engagement with certain project components and activities. This experimentation will serve as the basis for future research.

Enterprise social networks : a business model perspective

Enterprise Social Networks continue to be adopted by organisations looking to increase collaboration between employees, customers and industry partners. Offering a varied range of features and functionality, this technology can be distinguished by the underlying business models that providers of this software deploy. This study identifies and describes the different business models through an analysis of leading Enterprise Social Networks: Yammer, Chatter, SharePoint, Connections, Jive, Facebook and Twitter. A key contribution of this research is the identification of consumer and corporate models as extreme approaches. These findings align well with research on the adoption of Enterprise Social Networks that has discussed bottom-up and top-down approaches. Of specific interest are hybrid models that wrap a corporate model within a consumer model and may, therefore, provide synergies on both models. From a broader perspective, this can be seen as the merging of the corporate and consumer markets for IT products and services.

Multiscale investigation of microfilament networks disruption in living cells

Actin is the most abundantly distributed protein in living cells which plays critical roles in the cell interior force generation and transmission. The fracture mechanism of microfilament networks, whose principle component is actin, would provide insights which can contribute to the understandings of self-protective characters of cytoskeleton. In this study, molecular simulations are conducted to investigate the molecular mechanisms of disruption of microfilament networks from the viewpoint of biophysics. By employing a coarse-grained (CG) model of actin filament networks, we focused on the ultimate strength and crack growth mode of microfilament networks that have dependency on the crack length. It can be found that, the fracture mechanism of microfilament network has dependency on the structural properties of microfilament networks. The structure flaws marginally change the strength of microfilament networks which would explain the self-protective characters of cytoskeleton.

Co-production of actions and activities at airport security screening

In this paper we will examine passenger actions and activities at the security screening points of Australian domestic and international airports. Our findings and analysis provide a more complete understanding of the current airport passenger security screening experience. Data in this paper is comprised of field studies conducted at two Australian airports, one domestic and one international. Video data was collected by cameras situated either side of the security screening point. A total of one hundred and ninety-six passengers were observed. Two methods of analysis are used. First, the activities of passengers are coded and analysed to reveal the common activities at domestic and international security regimes and between quiet and busy periods. Second, observation of passenger activities is used to reveal uncommon aspects. The results show that passengers do more at security screening that being passively scanned. Passengers queue, unpack the required items from their bags and from their pockets, walk through the metal-detector, re-pack and occasionally return to be re-screened. For each of these activities, passengers must understand the procedures at the security screening point and must co-ordinate various actions and objects in time and space. Through this coordination passengers are active participants in making the security checkpoint function – they are co-producers of the security screening process.

Production of transgenic rice with rice ragged stunt virus synthetic resistance genes

Rice ragged stunt virus (RRSV) is an important pathogen of rice affecting its cultivation in South and South East Asia. An approach based on pathogen derived resistance (PDR) was used to produce RRSV resistant rice cultivars. Sequences from the coding region of RRSV genome segments 7 and 10 (non-structural genes), and 5, 8 and 9 (structural genes) were placed in sense or antisense orientation behind the plant expression promoters CaMV35S, RolC, Ubil, Actl and RBTV. Rice cultivars Taipei 309 and Chinsurah Boro II were transformed by biolistic and/or Agrobacterium-mediated delivery of one or more of these PDR gene constructs. A large number of transgenic lines were produced from calli derived from mature or immature embryos, co-bombarded with the marker gene hph encoding hygromycin resistance and RRSV PDR genes or co-cultivated with strains having the binary vector containing these two genes. Both Mendelian and non-Mendelian segregations were observed in transgenic progeny, especially with transgenic lines produced by biolistics. Preliminary tests conducted in China on selected transgenic lines indicate that plants with RRSV segment 5 antisense PDR gene confer RRSV resistance.

Co-creating knowledge online : approaches for community artists

Forming peer alliances to share and build knowledge is an important aspect of community arts practice, and these co-creation processes are increasingly being mediated by the internet. This paper offers guidance for practitioners who are interested in better utilising the internet to connect, share, and make new knowledge. It argues that new approaches are required to foster the organising activities that underpin online co-creation, building from the premise that people have become increasingly networked as individuals rather than in groups (Rainie and Wellman 2012: 6), and that these new ways of connecting enable new modes of peer-to-peer production and exchange. This position advocates that practitioners move beyond situating the internet as a platform for dissemination and a tool for co-creating media, to embrace its knowledge collaboration potential. Drawing on a design experiment I developed to promote online knowledge co-creation, this paper suggests three development phases – developing connections, developing ideas, and developing agility – to ground six methods. They are: switching and routing, engaging in small trades of ideas with networked individuals; organising, co-ordinating networked individuals and their data; beta-release, offering ‘beta’ artifacts as knowledge trades; beta-testing, trialing and modifying other peoples ‘beta’ ideas; adapting, responding to technological disruption; and, reconfiguring, embracing opportunities offered by technological disruption. These approaches position knowledge co-creation as another capability of the community artist, along with co-creating art and media.

Application of lean production to reducing operational waste in a tile manufacturing process

Roofing tile manufacturing is a mass production process with high operational and inventory wastes and costs. Due to huge operational costs, excessive inventory and wastes, and quality problems, roofing tile manufacturers are trying to implement lean manufacturing practice in their operations in order to remain competitive in an ncreasingly competitive global market. The aim of this research is to evaluate the possibility of reducing the operational and inventory costs of the tile manufacturing process through waste minimization. This paper analyses the current waste situation in a tile manufacturing process and develops current and future value stream mapping for such a process with a view to implementing lean principles in manufacturing. The focus of the approach is on cost reduction by eliminating non-value-added activities.

Predicting voltage unbalance impacts of plug-in electric vehicles penetration in residential low-voltage distribution networks

Plug-in electric vehicles will soon be connected to residential distribution networks in high quantities and will add to already overburdened residential feeders. However, as battery technology improves, plug-in electric vehicles will also be able to support networks as small distributed generation units by transferring the energy stored in their battery into the grid. Even though the increase in the plug-in electric vehicle connection is gradual, their connection points and charging/discharging levels are random. Therefore, such single-phase bidirectional power flows can have an adverse effect on the voltage unbalance of a three-phase distribution network. In this article, a voltage unbalance sensitivity analysis based on charging/discharging levels and the connection point of plug-in electric vehicles in a residential low-voltage distribution network is presented. Due to the many uncertainties in plug-in electric vehicle ratings and connection points and the network load, a Monte Carlo-based stochastic analysis is developed to predict voltage unbalance in the network in the presence of plug-in electric vehicles. A failure index is introduced to demonstrate the probability of non-standard voltage unbalance in the network due to plug-in electric vehicles.

Sampling designs on stream networks using the pseudo-Bayesian approach

Monitoring stream networks through time provides important ecological information. The sampling design problem is to choose locations where measurements are taken so as to maximise information gathered about physicochemical and biological variables on the stream network. This paper uses a pseudo-Bayesian approach, averaging a utility function over a prior distribution, in finding a design which maximizes the average utility. We use models for correlations of observations on the stream network that are based on stream network distances and described by moving average error models. Utility functions used reflect the needs of the experimenter, such as prediction of location values or estimation of parameters. We propose an algorithmic approach to design with the mean utility of a design estimated using Monte Carlo techniques and an exchange algorithm to search for optimal sampling designs. In particular we focus on the problem of finding an optimal design from a set of fixed designs and finding an optimal subset of a given set of sampling locations. As there are many different variables to measure, such as chemical, physical and biological measurements at each location, designs are derived from models based on different types of response variables: continuous, counts and proportions. We apply the methodology to a synthetic example and the Lake Eacham stream network on the Atherton Tablelands in Queensland, Australia. We show that the optimal designs depend very much on the choice of utility function, varying from space filling to clustered designs and mixtures of these, but given the utility function, designs are relatively robust to the type of response variable.

Broadcasting digital stories on Australian community television : the Digistories Anthology

Community-based arts and media movements have been intsrumental in building population-wide creative capacity for cultural development, social participation and social transformation in many parts of the world. Digital storytelling is a form of media practice that was pioneered in the United States at the intersection of these movements. It is described here as a ‘co-creative’ media production method. This description aims to differentiate the approaches to collaborative content creation that are used in community cultural development (CCD) and community media movements from those valued in professional and consumer modes of media production. Yet, the products of co-creative practices, such as digital stories, do not circulate widely through existing media networks or through the newer social media networks that Australian CCD and community media movements anticipated by at least twenty years. The complex politics of story ownership are one of a number of factors that often render ‘publication’ a secondary consideration in the making of digital stories. The possibility of ‘downstream’ use and re-use of stories in other networks is not usually considered in initial planning and development processes. As landmark projects such as Capture Wales indicate, even where stories are made for broadcast outcomes, television can be a problematic window for exhibiting digital stories. Scepticism about the brave new world of reality television and user generated content also circulates in digital storytelling networks, especially when it comes to ethical concerns for managing the risks of harm associated with widespread distribution of digital stories to indiscriminate publics. This publication reports on a collaborative action research project that took a closer look at some of the constraints relating to the problems of re-purposing digital stories for television. It focussed on ‘best practice’ for managing the risks of harm to storytellers in the process of re-purposing digital stories for broadcast on community television.

Bayesian networks in environmental and resource management

This overview article for the special series “Bayesian Networks in Environmental and Resource Management” reviews 7 case study articles with the aim to compare Bayesian network (BN) applications to different environmental and resource management problems from around the world. The article discusses advances in the last decade in the use of BNs as applied to environmental and resource management. We highlight progress in computational methods, best-practices for model design and model communication. We review several research challenges to the use of BNs in environmental and resource management that we think may find a solution in the near future with further research attention.