A Bayesian network approach to modelling temporal behaviour of Lyngbya majuscula bloom initiation

Lyngbya majuscula is a cyanobacterium (blue-green algae) occurring naturally in tropical and subtropical coastal areas worldwide. Deception Bay, in Northern Moreton Bay, Queensland, has a history of Lyngbya blooms, and forms a case study for this investigation. The South East Queensland (SEQ) Healthy Waterways Partnership, collaboration between government, industry, research and the community, was formed to address issues affecting the health of the river catchments and waterways of South East Queensland. The Partnership coordinated the Lyngbya Research and Management Program (2005-2007) which culminated in a Coastal Algal Blooms (CAB) Action Plan for harmful and nuisance algal blooms, such as Lyngbya majuscula. This first phase of the project was predominantly of a scientific nature and also facilitated the collection of additional data to better understand Lyngbya blooms. The second phase of this project, SEQ Healthy Waterways Strategy 2007-2012, is now underway to implement the CAB Action Plan and as such is more management focussed. As part of the first phase of the project, a Science model for the initiation of a Lyngbya bloom was built using Bayesian Networks (BN). The structure of the Science Bayesian Network was built by the Lyngbya Science Working Group (LSWG) which was drawn from diverse disciplines. The BN was then quantified with annual data and expert knowledge. Scenario testing confirmed the expected temporal nature of bloom initiation and it was recommended that the next version of the BN be extended to take this into account. Elicitation for this BN thus occurred at three levels: design, quantification and verification. The first level involved construction of the conceptual model itself, definition of the nodes within the model and identification of sources of information to quantify the nodes. The second level included elicitation of expert opinion and representation of this information in a form suitable for inclusion in the BN. The third and final level concerned the specification of scenarios used to verify the model. The second phase of the project provides the opportunity to update the network with the newly collected detailed data obtained during the previous phase of the project. Specifically the temporal nature of Lyngbya blooms is of interest. Management efforts need to be directed to the most vulnerable periods to bloom initiation in the Bay. To model the temporal aspects of Lyngbya we are using Object Oriented Bayesian networks (OOBN) to create ‘time slices’ for each of the periods of interest during the summer. OOBNs provide a framework to simplify knowledge representation and facilitate reuse of nodes and network fragments. An OOBN is more hierarchical than a traditional BN with any sub-network able to contain other sub-networks. Connectivity between OOBNs is an important feature and allows information flow between the time slices. This study demonstrates more sophisticated use of expert information within Bayesian networks, which combine expert knowledge with data (categorized using expert-defined thresholds) within an expert-defined model structure. Based on the results from the verification process the experts are able to target areas requiring greater precision and those exhibiting temporal behaviour. The time slices incorporate the data for that time period for each of the temporal nodes (instead of using the annual data from the previous static Science BN) and include lag effects to allow the effect from one time slice to flow to the next time slice. We demonstrate a concurrent steady increase in the probability of initiation of a Lyngbya bloom and conclude that the inclusion of temporal aspects in the BN model is consistent with the perceptions of Lyngbya behaviour held by the stakeholders. This extended model provides a more accurate representation of the increased risk of algal blooms in the summer months and show that the opinions elicited to inform a static BN can be readily extended to a dynamic OOBN, providing more comprehensive information for decision makers.

Welfare surveillance, income management and new paternalism in Australia

This article discusses the situation of income support claimants in Australia, constructed as faulty citizens and flawed welfare subjects. Many are on the receiving end of complex, multi-layered forms of surveillance aimed at securing socially responsible and compliant behaviours. In Australia, as in other Western countries, neoliberal economic regimes with their harsh and often repressive treatment of welfare recipients operate in tandem with a burgeoning and costly arsenal of CCTV and other surveillance and governance assemblages. Through a program of ‘Income Management’, initially targeting (mainly) Indigenous welfare recipients in Australia’s Northern Territory, the BasicsCard (administered by Centrelink, on behalf of the Australian Federal Government’s Department of Human Services) is one example of this welfare surveillance. The scheme operates by ‘quarantining’ a percentage of a claimant’s welfare entitlements to be spent by way of the BasicsCard on ‘approved’ items only. The BasicsCard scheme raises significant questions about whether it is possible to encourage people to take responsibility for themselves if they no longer have real control over the most important aspects of their lives. Some Indigenous communities have resisted the BasicsCard, criticising it because the imposition of income management leads to a loss of trust, dignity, and individual agency. Further, income management of individuals by the welfare state contradicts the purported aim that they become less ‘welfare dependent’ and more ‘self-reliant’. In highlighting issues around compulsory income management this paper makes a contribution to the largely under discussed area of income management and welfare surveillance, with its propensity for function creep, garnering large volumes of data on BasicsCard user’s approved (and declined) purchasing decisions, complete with dates, amounts, times and locations.

Much ado about nothing? Tracing the progress of innovations borne on enterprise social network sites

Enterprise social networks are organizationally bounded online platforms for users to interact with another and maintain interpersonal relationships. The allure of these technologies is often seen in intra-organizational communication, collaboration and innovation. How these technologies actually support organizational innovation efforts remains unclear. A specific challenge is whether digital content on these platforms converts to actual innovation development efforts. In this study we set out to examine innovation-centric content flows on enterprise social networking platforms, and advance a conceptual model that seeks to explain which innovation conveyed in the digital content will traverse from the digital platform into regular processes. We describe important constructs of our model and offer strategies for the operationalization of the constructs. We conclude with an outlook to our ongoing empirical study that will explore and validate the key propositions of our model, and we sketch some potential implications for industry and academia.

Brisbane Macroscopic Fundamental Diagram : empirical findings on network partitioning and incident detection

The Macroscopic Fundamental Diagram (MFD) relates space-mean density and flow, and the existence with dynamic features was confirmed in congested urban network in downtown Yokohama with real data set. Since the MFD represents the area-wide network traffic performances, studies on perimeter control strategies and an area traffic state estimation utilizing the MFD concept has been reported. However, limited works have been reported on real world example from signalised arterial network. This paper fuses data from multiple sources (Bluetooth, Loops and Signals) and develops a framework for the development of the MFD for Brisbane, Australia. Existence of the MFD in Brisbane arterial network is confirmed. Different MFDs (from whole network and several sub regions) are evaluated to discover the spatial partitioning in network performance representation. The findings confirmed the usefulness of appropriate network partitioning for traffic monitoring and incident detections. The discussion addressed future research directions

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.

Modelling for the electricity distribution network

Global awareness for cleaner and renewable energy is transforming the electricity sector at many levels. New technologies are being increasingly integrated into the electricity grid at high, medium and low voltage levels, new taxes on carbon emissions are being introduced and individuals can now produce electricity, mainly through rooftop photovoltaic (PV) systems. While leading to improvements, these changes also introduce challenges, and a question that often rises is ‘how can we manage this constantly evolving grid?’ The Queensland Government and Ergon Energy, one of the two Queensland distribution companies, have partnered with some Australian and German universities on a project to answer this question in a holistic manner. The project investigates the impact the integration of renewables and other new technologies has on the physical structure of the grid, and how this evolving system can be managed in a sustainable and economical manner. To aid understanding of what the future might bring, a software platform has been developed that integrates two modelling techniques: agent-based modelling (ABM) to capture the characteristics of the different system units accurately and dynamically, and particle swarm optimization (PSO) to find the most economical mix of network extension and integration of distributed generation over long periods of time. Using data from Ergon Energy, two types of networks (3 phase, and Single Wired Earth Return or SWER) have been modelled; three-phase networks are usually used in dense networks such as urban areas, while SWER networks are widely used in rural Queensland. Simulations can be performed on these networks to identify the required upgrades, following a three-step process: a) what is already in place and how it performs under current and future loads, b) what can be done to manage it and plan the future grid and c) how these upgrades/new installations will perform over time. The number of small-scale distributed generators, e.g. PV and battery, is now sufficient (and expected to increase) to impact the operation of the grid, which in turn needs to be considered by the distribution network manager when planning for upgrades and/or installations to stay within regulatory limits. Different scenarios can be simulated, with different levels of distributed generation, in-place as well as expected, so that a large number of options can be assessed (Step a). Once the location, sizing and timing of assets upgrade and/or installation are found using optimisation techniques (Step b), it is possible to assess the adequacy of their daily performance using agent-based modelling (Step c). One distinguishing feature of this software is that it is possible to analyse a whole area at once, while still having a tailored solution for each of the sub-areas. To illustrate this, using the impact of battery and PV can have on the two types of networks mentioned above, three design conditions can be identified (amongst others): · Urban conditions o Feeders that have a low take-up of solar generators, may benefit from adding solar panels o Feeders that need voltage support at specific times, may be assisted by installing batteries · Rural conditions - SWER network o Feeders that need voltage support as well as peak lopping may benefit from both battery and solar panel installations. This small example demonstrates that no single solution can be applied across all three areas, and there is a need to be selective in which one is applied to each branch of the network. This is currently the function of the engineer who can define various scenarios against a configuration, test them and iterate towards an appropriate solution. Future work will focus on increasing the level of automation in identifying areas where particular solutions are applicable.

Can Business Continuity Management Create Reliability in Airports? (Issues from Theory into Practice)

The advances made within the aviation industry over the past several decades have significantly improved the availability, affordability and convenience of air travel and have been greatly beneficial in both social and economic terms. Air transport has developed into an irreplaceable service being relied on by millions of people each day and as such airports have become critical elements of national infrastructure to facilitate the movement of people and goods. As components of critical infrastructure (CI), airports are integral parts of a national economy supporting regional as well as national trade, commercial activity and employment. Therefore, any disruption or crisis which impacts the continuity of operations at airports can have significant negative consequences for the airport as a business, for the local economy and other nodes of transport infrastructure as well as for society. Due to the highly dynamic and volatile environment in which airports operate in, the aviation industry has faced many different challenges over the years ranging from terrorist attacks such as September 11, to health crises such as the SARS epidemic to system breakdowns such as the recent computer system outage at Virgin Blue Airlines in Australia. All these events have highlighted the vulnerability of airport systems to a range of disturbances as well as the gravity and widespread impact of any kind of discontinuity in airport functions. Such incidents thus emphasise the need for increasing resilience and reliability of airports and ensuring business continuity in the event of a crisis...

Applying quantile regression for modeling equivalent property damage only crashes to identify accident blackspots

Hot spot identification (HSID) aims to identify potential sites—roadway segments, intersections, crosswalks, interchanges, ramps, etc.—with disproportionately high crash risk relative to similar sites. An inefficient HSID methodology might result in either identifying a safe site as high risk (false positive) or a high risk site as safe (false negative), and consequently lead to the misuse the available public funds, to poor investment decisions, and to inefficient risk management practice. Current HSID methods suffer from issues like underreporting of minor injury and property damage only (PDO) crashes, challenges of accounting for crash severity into the methodology, and selection of a proper safety performance function to model crash data that is often heavily skewed by a preponderance of zeros. Addressing these challenges, this paper proposes a combination of a PDO equivalency calculation and quantile regression technique to identify hot spots in a transportation network. In particular, issues related to underreporting and crash severity are tackled by incorporating equivalent PDO crashes, whilst the concerns related to the non-count nature of equivalent PDO crashes and the skewness of crash data are addressed by the non-parametric quantile regression technique. The proposed method identifies covariate effects on various quantiles of a population, rather than the population mean like most methods in practice, which more closely corresponds with how black spots are identified in practice. The proposed methodology is illustrated using rural road segment data from Korea and compared against the traditional EB method with negative binomial regression. Application of a quantile regression model on equivalent PDO crashes enables identification of a set of high-risk sites that reflect the true safety costs to the society, simultaneously reduces the influence of under-reported PDO and minor injury crashes, and overcomes the limitation of traditional NB model in dealing with preponderance of zeros problem or right skewed dataset.

Perspectives on research in project management : the nine schools

This paper demonstrates that project management is a developing field of academic study in management, of considerable diversity and richness, which can make a valuable contribution to the development of management knowledge, as well as being of considerable economic importance. The paper reviews the substantial progress and trends of research in the subject, which has been grouped into nine major schools of thought: optimization, modelling, governance, behaviour, success, decision, process, contingency, and marketing. The paper addresses interactions between the different schools and with other related management fields, and provides insights into current and potential research in each and across these schools.

Cross-layer design for traffic management in wireless networked control systems

Wireless networked control systems (WNCSs) have been increasingly deployed in industrial applications. As they require timely data packet transmissions, it is difficult to make efficient use of the limited channel resources, particularly in contention based wireless networks in the layered network architecture. Aiming to maintain the WNCSs under critical real-time traffic condition at which the WNCSs marginally meet the real-time requirements, a cross-layer design (CLD) approach is presented in this paper to adaptively adjust the control period to achieve improved channel utilization while still maintaining effective and timely packet transmissions. The effectiveness of the proposed approach is demonstrated through simulation studies.

Australasian nutrition research for prevention and management of child obesity : innovation and progress in the last decade

The Food and Nutrition stream of Australasian Child and Adolescent Obesity Research Network (ACAORN) aims to improve the quality of dietary methodologies and the reporting of dietary intake within Australasian child obesity research (http://www.acaorn.org.au/streams/nutrition/). With 2012 marking ACAORN’s 10th anniversary, this commentary profiles a selection of child obesity nutrition research published over the last decade by Food and Nutrition Stream members. In addition, stream activities have included the development of an online selection guide to assist researchers in their selection of appropriate dietary intake methodologies (http://www.acaorn.org.au/streams/nutrition/dietary-intake/index.php). The quantity and quality of research to guide effective child obesity prevention and treatment has increased substantially over the last decade. ACAORN provides a successful case study of how research networks can provide a collegial atmosphere to foster and co-ordinate research efforts in an otherwise competitive environment.

Towards networked governance : improving interagency communication and collaboration for disaster risk management and climate change adaptation in Australia

Major disasters, such as bushfires or floods, place significant stress on scarce public resources. Climate change is likely to exacerbate this stress. An integrated approach to disaster risk management (DRM) and climate change adaptation (CCA) could reduce the stress by encouraging the more efficient use of pooled resources and expertise. A comparative analysis of three extreme climate-related events that occurred in Australia between 2009 and 2011 indicated that a strategy to improve interagency communication and collaboration would be a key factor in this type of policy/planning integration. These findings are in accord with the concepts of Joined-up Government and Network Governance. Five key reforms are proposed: developing a shared policy vision; adopting multi-level planning; integrating legislation; networking organisations; and establishing cooperative funding. These reforms are examined with reference to the related research literature in order to identify potential problems associated with their implementation. The findings are relevant for public policy generally but are particularly useful for CCA and DRM.

Voltage regulation, power balancing and battery storage discharge control by smart demand side management and multi-objective decision making

A novel intelligent online demand side management system is proposed for peak load management. The method also regulates the network voltage, balances the power in three phases and coordinates the battery storage discharge within the network. This method uses low cost controllers with low bandwidth two-way communication installed in costumers' premises and at distribution transformers to manage the peak load while maximizing customer satisfaction. A multi-objective decision making process is proposed to select the load(s) to be delayed or controlled. The efficacy of the proposed control system is verified through an event-based developed simulation in Matlab.

On-line Demand Management of Low Voltage Residential Distribution Networks in Smart Grids

A novel intelligent online demand management system is discussed in this chapter for peak load management in low voltage residential distribution networks based on the smart grid concept. The discussed system also regulates the network voltage, balances the power in three phases and coordinates the energy storage within the network. This method uses low cost controllers, with two-way communication interfaces, installed in costumers’ premises and at distribution transformers to manage the peak load while maximizing customer satisfaction. A multi-objective decision making process is proposed to select the load(s) to be delayed or controlled. The efficacy of the proposed control system is verified by a MATLAB-based simulation which includes detailed modeling of residential loads and the network.