Bayesian inference of traffic volumes based on Bluetooth data

The study of the relationship between macroscopic traffic parameters, such as flow, speed and travel time, is essential to the understanding of the behaviour of freeway and arterial roads. However, the temporal dynamics of these parameters are difficult to model, especially for arterial roads, where the process of traffic change is driven by a variety of variables. The introduction of the Bluetooth technology into the transportation area has proven exceptionally useful for monitoring vehicular traffic, as it allows reliable estimation of travel times and traffic demands. In this work, we propose an approach based on Bayesian networks for analyzing and predicting the complex dynamics of flow or volume, based on travel time observations from Bluetooth sensors. The spatio-temporal relationship between volume and travel time is captured through a first-order transition model, and a univariate Gaussian sensor model. The two models are trained and tested on travel time and volume data, from an arterial link, collected over a period of six days. To reduce the computational costs of the inference tasks, volume is converted into a discrete variable. The discretization process is carried out through a Self-Organizing Map. Preliminary results show that a simple Bayesian network can effectively estimate and predict the complex temporal dynamics of arterial volumes from the travel time data. Not only is the model well suited to produce posterior distributions over single past, current and future states; but it also allows computing the estimations of joint distributions, over sequences of states. Furthermore, the Bayesian network can achieve excellent prediction, even when the stream of travel time observation is partially incomplete.

Australian Screen Producers Survey : online interactive

There is growing scholarly interest in the everyday work undertaken by screen producers in part prompted by disciplinary shifts (the ‘material turn’, the rise of creative industries research) and in part by major transformations in the business of media production and consumption in recent years. However, the production cultures and motivations of screen producers, particularly those working in emergent online and convergent media markets, remain poorly understood. The 2012 Australian Screen Producer survey, building upon research undertaken in the Australian Screen Content Producer Survey conducted in 2009, was a nation-wide survey-based study of screen content producers working in four industry segments: film, television, corporate and new media production. The broad objectives of the 2012 Australian Producer Survey study were to: • Provide deeper and more detailed analysis into the nature of digital media producers and their practices and how these findings compare to the practices of established screen media producers; • Interrogate issues around the pace of industry change, industry sentiment and how producers are adapting to a changing marketplace; and • Offer insight into the transitional pathways of established media producers into production for digital media markets. The Australian Screen Producer Survey Online Interactive provides users (principally filmmakers, scholars and policymakers) with direct access to raw survey data through an interactive website that allows them to customise queries according to particular interests. The Online Interactive therefore provides customisable findings – unlike ‘static’ research outputs – delineating the practices, attitudes, strategies, and aspirations of screen producers working in feature film, television and corporate production as well as those operating in an increasingly convergent digital media marketplace. The survey was developed by researchers at the ARC Centre of Excellence for Creative Industries and Innovation (CCI), Queensland University of Technology, Deakin University, the Centre for Screen Business at Australian Film Television and Radio School (AFTRS) and was undertaken in association with Bergent Research. The Online Interactive website (http://screenproducersurvey.com/) was developed with support from the Centre for Memory Imagination and Invention (CMII).

Second-order inelastic analysis of composite framed structures based on the refined plastic hinge method

Composite steel-concrete structures experience non-linear effects which arise from both instability-related geometric non-linearity and from material non-linearity in all of their component members. Because of this, conventional design procedures cannot capture the true behaviour of a composite frame throughout its full loading range, and so a procedure to account for those non-linearities is much needed. This paper therefore presents a numerical procedure capable of addressing geometric and material non-linearities at the strength limit state based on the refined plastic hinge method. Different material non-linearity for different composite structural components such as T-beams, concrete-filled tubular (CFT) and steel-encased reinforced concrete (SRC) sections can be treated using a routine numerical procedure for their section properties in this plastic hinge approach. Simple and conservative initial and full yield surfaces for general composite sections are proposed in this paper. The refined plastic hinge approach models springs at the ends of the element which are activated when the surface defining the interaction of bending and axial force at first yield is reached; a transition from the first yield interaction surface to the fully plastic interaction surface is postulated based on a proposed refined spring stiffness, which formulates the load-displacement relation for material non-linearity under the interaction of bending and axial actions. This produces a benign method for a beam-column composite element under general loading cases. Another main feature of this paper is that, for members containing a point of contraflexure, its location is determined with a simple application of the method herein and a node is then located at this position to reproduce the real flexural behaviour and associated material non-linearity of the member. Recourse is made to an updated Lagrangian formulation to consider geometric non-linear behaviour and to develop a non-linear solution strategy. The formulation with the refined plastic hinge approach is efficacious and robust, and so a full frame analysis incorporating geometric and material non-linearity is tractable. By way of contrast, the plastic zone approach possesses the drawback of strain-based procedures which rely on determining plastic zones within a cross-section and which require lengthwise integration. Following development of the theory, its application is illustrated with a number of varied examples.

A reference station-based GNSS computing mode to support unified precise point positioning and real-time kinematic services

Currently, the GNSS computing modes are of two classes: network-based data processing and user receiver-based processing. A GNSS reference receiver station essentially contributes raw measurement data in either the RINEX file format or as real-time data streams in the RTCM format. Very little computation is carried out by the reference station. The existing network-based processing modes, regardless of whether they are executed in real-time or post-processed modes, are centralised or sequential. This paper describes a distributed GNSS computing framework that incorporates three GNSS modes: reference station-based, user receiver-based and network-based data processing. Raw data streams from each GNSS reference receiver station are processed in a distributed manner, i.e., either at the station itself or at a hosting data server/processor, to generate station-based solutions, or reference receiver-specific parameters. These may include precise receiver clock, zenith tropospheric delay, differential code biases, ambiguity parameters, ionospheric delays, as well as line-of-sight information such as azimuth and elevation angles. Covariance information for estimated parameters may also be optionally provided. In such a mode the nearby precise point positioning (PPP) or real-time kinematic (RTK) users can directly use the corrections from all or some of the stations for real-time precise positioning via a data server. At the user receiver, PPP and RTK techniques are unified under the same observation models, and the distinction is how the user receiver software deals with corrections from the reference station solutions and the ambiguity estimation in the observation equations. Numerical tests demonstrate good convergence behaviour for differential code bias and ambiguity estimates derived individually with single reference stations. With station-based solutions from three reference stations within distances of 22–103 km the user receiver positioning results, with various schemes, show an accuracy improvement of the proposed station-augmented PPP and ambiguity-fixed PPP solutions with respect to the standard float PPP solutions without station augmentation and ambiguity resolutions. Overall, the proposed reference station-based GNSS computing mode can support PPP and RTK positioning services as a simpler alternative to the existing network-based RTK or regionally augmented PPP systems.

A simulation-based large deflection and inelastic analysis of steel frames under fire

This paper presents an accurate and robust geometric and material nonlinear formulation to predict structural behaviour of unprotected steel members at elevated temperatures. A fire analysis including large displacement effects for frame structures is presented. This finite element formulation of beam-column elements is based on the plastic hinge approach to model the elasto-plastic strain-hardening material behaviour. The Newton-Raphson method allowing for the thermal-time dependent effect was employed for the solution of the non-linear governing equations for large deflection in thermal history. A combined incremental and total formulation for determining member resistance is employed in this nonlinear solution procedure for the efficient modeling of nonlinear effects. Degradation of material strength with increasing temperature is simulated by a set of temperature-stress-strain curves according to both ECCS and BS5950 Part 8, which implicitly allows for creep deformation. The effects of uniform or non-uniform temperature distribution over the section of the structural steel member are also considered. Several numerical and experimental verifications are presented.

Performance-based structural fire design of steel frames using conventional computer software

Fire incident in buildings is common, so the fire safety design of the framed structure is imperative, especially for the unprotected or partly protected bare steel frames. However, software for structural fire analysis is not widely available. As a result, the performance-based structural fire design is urged on the basis of using user-friendly and conventional nonlinear computer analysis programs so that engineers do not need to acquire new structural analysis software for structural fire analysis and design. The tool is desired to have the capacity of simulating the different fire scenarios and associated detrimental effects efficiently, which includes second-order P-D and P-d effects and material yielding. Also the nonlinear behaviour of large-scale structure becomes complicated when under fire, and thus its simulation relies on an efficient and effective numerical analysis to cope with intricate nonlinear effects due to fire. To this end, the present fire study utilizes a second order elastic/plastic analysis software NIDA to predict structural behaviour of bare steel framed structures at elevated temperatures. This fire study considers thermal expansion and material degradation due to heating. Degradation of material strength with increasing temperature is included by a set of temperature-stress-strain curves according to BS5950 Part 8 mainly, which implicitly allows for creep deformation. This finite element stiffness formulation of beam-column elements is derived from the fifth-order PEP element which facilitates the computer modeling by one member per element. The Newton-Raphson method is used in the nonlinear solution procedure in order to trace the nonlinear equilibrium path at specified elevated temperatures. Several numerical and experimental verifications of framed structures are presented and compared against solutions in literature. The proposed method permits engineers to adopt the performance-based structural fire analysis and design using typical second-order nonlinear structural analysis software.

Internet-based surveillance systems for monitoring emerging infectious diseases

Emerging infectious diseases present a complex challenge to public health officials and governments; these challenges have been compounded by rapidly shifting patterns of human behaviour and globalisation. The increase in emerging infectious diseases has led to calls for new technologies and approaches for detection, tracking, reporting, and response. Internet-based surveillance systems offer a novel and developing means of monitoring conditions of public health concern, including emerging infectious diseases. We review studies that have exploited internet use and search trends to monitor two such diseases: influenza and dengue. Internet-based surveillance systems have good congruence with traditional surveillance approaches. Additionally, internet-based approaches are logistically and economically appealing. However, they do not have the capacity to replace traditional surveillance systems; they should not be viewed as an alternative, but rather an extension. Future research should focus on using data generated through internet-based surveillance and response systems to bolster the capacity of traditional surveillance systems for emerging infectious diseases.

Using GPS technology to (re)-examine operational definitions of 'neighbourhood' in place-based health research

BACKGROUND Inconsistencies in research findings on the impact of the built environment on walking across the life course may be methodologically driven. Commonly used methods to define 'neighbourhood', from which built environment variables are measured, may not accurately represent the spatial extent to which the behaviour in question occurs. This paper aims to provide new methods for spatially defining 'neighbourhood' based on how people use their surrounding environment. RESULTS Informed by Global Positioning Systems (GPS) tracking data, several alternative neighbourhood delineation techniques were examined (i.e., variable width, convex hull and standard deviation buffers). Compared with traditionally used buffers (i.e., circular and polygon network), differences were found in built environment characteristics within the newly created 'neighbourhoods'. Model fit statistics indicated that exposure measures derived from alternative buffering techniques provided a better fit when examining the relationship between land-use and walking for transport or leisure. CONCLUSIONS This research identifies how changes in the spatial extent from which built environment measures are derived may influence walking behaviour. Buffer size and orientation influences the relationship between built environment measures and walking for leisure in older adults. The use of GPS data proved suitable for re-examining operational definitions of neighbourhood.

Building adaptable agent-based models – application to the electricity distribution network

Agent-based modelling (ABM), like other modelling techniques, is used to answer specific questions from real world systems that could otherwise be expensive or impractical. Its recent gain in popularity can be attributed to some degree to its capacity to use information at a fine level of detail of the system, both geographically and temporally, and generate information at a higher level, where emerging patterns can be observed. This technique is data-intensive, as explicit data at a fine level of detail is used and it is computer-intensive as many interactions between agents, which can learn and have a goal, are required. With the growing availability of data and the increase in computer power, these concerns are however fading. Nonetheless, being able to update or extend the model as more information becomes available can become problematic, because of the tight coupling of the agents and their dependence on the data, especially when modelling very large systems. One large system to which ABM is currently applied is the electricity distribution where thousands of agents representing the network and the consumers’ behaviours are interacting with one another. A framework that aims at answering a range of questions regarding the potential evolution of the grid has been developed and is presented here. It uses agent-based modelling to represent the engineering infrastructure of the distribution network and has been built with flexibility and extensibility in mind. What distinguishes the method presented here from the usual ABMs is that this ABM has been developed in a compositional manner. This encompasses not only the software tool, which core is named MODAM (MODular Agent-based Model) but the model itself. Using such approach enables the model to be extended as more information becomes available or modified as the electricity system evolves, leading to an adaptable model. Two well-known modularity principles in the software engineering domain are information hiding and separation of concerns. These principles were used to develop the agent-based model on top of OSGi and Eclipse plugins which have good support for modularity. Information regarding the model entities was separated into a) assets which describe the entities’ physical characteristics, and b) agents which describe their behaviour according to their goal and previous learning experiences. This approach diverges from the traditional approach where both aspects are often conflated. It has many advantages in terms of reusability of one or the other aspect for different purposes as well as composability when building simulations. For example, the way an asset is used on a network can greatly vary while its physical characteristics are the same – this is the case for two identical battery systems which usage will vary depending on the purpose of their installation. While any battery can be described by its physical properties (e.g. capacity, lifetime, and depth of discharge), its behaviour will vary depending on who is using it and what their aim is. The model is populated using data describing both aspects (physical characteristics and behaviour) and can be updated as required depending on what simulation is to be run. For example, data can be used to describe the environment to which the agents respond to – e.g. weather for solar panels, or to describe the assets and their relation to one another – e.g. the network assets. Finally, when running a simulation, MODAM calls on its module manager that coordinates the different plugins, automates the creation of the assets and agents using factories, and schedules their execution which can be done sequentially or in parallel for faster execution. Building agent-based models in this way has proven fast when adding new complex behaviours, as well as new types of assets. Simulations have been run to understand the potential impact of changes on the network in terms of assets (e.g. installation of decentralised generators) or behaviours (e.g. response to different management aims). While this platform has been developed within the context of a project focussing on the electricity domain, the core of the software, MODAM, can be extended to other domains such as transport which is part of future work with the addition of electric vehicles.

An extensible framework for analysing resource behaviour using event logs

Business processes depend on human resources and managers must regularly evaluate the performance of their employees based on a number of measures, some of which are subjective in nature. As modern organisations use information systems to automate their business processes and record information about processes’ executions in event logs, it now becomes possible to get objective information about resource behaviours by analysing data recorded in event logs. We present an extensible framework for extracting knowledge from event logs about the behaviour of a human resource and for analysing the dynamics of this behaviour over time. The framework is fully automated and implements a predefined set of behavioural indicators for human resources. It also provides a means for organisations to define their own behavioural indicators, using the conventional Structured Query Language, and a means to analyse the dynamics of these indicators. The framework's applicability is demonstrated using an event log from a German bank.

Study protocol : a randomised controlled trial of a theory-based online intervention to improve sun safety among Australian adults

Background The effects of exposure to ultraviolet radiation are a significant concern in Australia which has one of the highest incidences of skin cancer in the world. Despite most skin cancers being preventable by encouraging consistent adoption of sun-protective behaviours, incidence rates are not decreasing. There is a dearth of research examining the factors involved in engaging in sun-protective behaviours. Further, online multi-behavioural theory-based interventions have yet to be explored fully as a medium for improving sun-protective behaviour in adults. This paper presents the study protocol of a randomised controlled trial of an online intervention based on the Theory of Planned Behaviour (TPB) that aims to improve sun safety among Australian adults. Methods/Design Approximately 420 adults aged 18 and over and predominantly from Queensland, Australia, will be recruited and randomised to the intervention (n = 200), information only (n = 200) or the control group (n = 20). The intervention focuses on encouraging supportive attitudes and beliefs toward sun-protective behaviour, fostering perceptions of normative support for sun protection, and increasing perceptions of control/self-efficacy over sun protection. The intervention will be delivered online over a single session. Data will be collected immediately prior to the intervention (Time 1), immediately following the intervention (Time 1b), and one week (Time 2) and one month (Time 3) post-intervention. Primary outcomes are intentions to sun protect and sun-protective behaviour. Secondary outcomes are the participants’ attitudes toward sun protection, perceptions of normative support for sun protection (i.e. subjective norms, group norms, personal norms and image norms) and perceptions of control/self-efficacy toward sun protection. Discussion The study will contribute to an understanding of the effectiveness of a TPB-based online intervention to improve Australian adults’ sun-protective behaviour. Trials registry Australian and New Zealand Trials Registry number ACTRN12613000470796

Typology of phishing email victims based on their behavioural response

A victim of phishing emails could be subjected to money loss and identity theft. This paper investigates the different types of phishing email victims, with the goal of increasing such victims' defences. To obtain this kind of information, an experiment which involves sending a phishing email to participants is conducted. Quantitative and qualitative methods are also used to collect users' information. A model for detecting deception has been employed to understand victims' behaviour. This paper reports the qualitative results. The findings suggest that victims of phishing emails do not always exhibit the same vulnerability. The cause of being a victim is a result of three weaknesses in the detection process: (1) lack of knowledge; (2) weak confirmation channel, and; (3) victims' high propensity towards risk-taking. Therefore, it is suggested that users be provided with suitable confirmation channels and be more risk averse in their behaviour so that they would not fall victim to phishing emails.

Impact of passenger group dynamics on an airport evacuation process using an agent-based model

The safety of passengers is a major concern to airports. In the event of crises, having an effective and efficient evacuation process in place can significantly aid in enhancing passenger safety. Hence, it is necessary for airport operators to have an in-depth understanding of the evacuation process of their airport terminal. Although evacuation models have been used in studying pedestrian behaviour for decades, little research has been done in considering the evacuees’ group dynamics and the complexity of the environment. In this paper, an agent-based model is presented to simulate passenger evacuation process. Different exits were allocated to passengers based on their location and security level. The simulation results show that the evacuation time can be influenced by passenger group dynamics. This model also provides a convenient way to design airport evacuation strategy and examine its efficiency. The model was created using AnyLogic software and its parameters were initialised using recent research data published in the literature.

An intuitive multi-touch surface and gesture based interaction for video surveillance systems

This paper discusses the idea and demonstrates an early prototype of a novel method of interacting with security surveillance footage using natural user interfaces in place of traditional mouse and keyboard interaction. Current surveillance monitoring stations and systems provide the user with a vast array of video feeds from multiple locations on a video wall, relying on the user’s ability to distinguish locations of the live feeds from experience or list based key-value pair of location and camera IDs. During an incident, this current method of interaction may cause the user to spend increased amounts time obtaining situational and location awareness, which is counter-productive. The system proposed in this paper demonstrates how a multi-touch screen and natural interaction can enable the surveillance monitoring station users to quickly identify the location of a security camera and efficiently respond to an incident.

Assessing the immediate and short-term impact of flooding on residential property participant behaviour

The past decade has seen an increase in the number of significant natural disasters that have caused considerable loss of life as well as damage to all property markets in the affected areas. In many cases, these natural disasters have not only caused significant property damage, but in numerous cases, have resulted in the total destruction of the property in the location. With these disasters attracting considerable media attention, the public are more aware of where these affected property markets are, as well as the overall damage to properties that have been damaged or destroyed. This heightened level of awareness has to have an impact on the participants in the property market, whether a developer, vendor seller or investor. To assess this issue, a residential property market that has been affected by a significant natural disaster over the past 2 years has been analysed to determine the overall impact of the disaster on buyer, renter and vendor behaviour, as well as prices in these residential markets. This paper is based on data from the Brisbane flood in January 2011. This natural disaster resulted in loss of life and partial and total devastation of considerable residential property sectors. Data for the research have been based on the residential sales and rental listings for each week of the study period to determine the level of activity in the specific property sectors, and these are also compared to the median house prices for the various suburbs for the same period based on suburbs being either flood affected or flood free. As there are 48 suburbs included in the study, it has been possible to group these suburbs on a socio-economic basis to determine possible differences due to location and value. Data were accessed from realestate.com.au, a free real estate site that provides details of current rental and sales listings on a suburb basis, RP Data a commercial property sales database and the Australian Bureau of Statistics. The paper found that sales listings fell immediately after the flood in the affected areas, but there was no corresponding fall or increase in sales listings in the flood-free suburbs. There was a significant decrease in the number of rental listings follow the flood as affected parties sought alternate accommodation. The greatest fall in rental listings was in areas close to the flood-affected suburbs indicating the desire to be close to the flooded property during the repair period.