Evaluation of an Augmented Reality Collaborative Process Modelling System

Identifying, modelling and documenting business processes usually requires the collaboration of many stakeholders that may be spread across companies in inter-organizational business settings. While there are many process modelling tools available, the support they provide for remote collaboration is still limited. This paper investigates the application of virtual environment and augmented reality technologies to remote business process modelling, with an aim to assisting common collaboration tasks by providing an increased sense of immersion in a shared workspace. We report on the evaluation of a prototype system with five key informants. The results indicate that this approach to business process modelling is suited to remote collaborative task settings, and stakeholders may indeed benefit from using augmented reality interfaces.

Food modelling systems to assess menus in well population groups : not all black and white

Food modelling systems such as the Core Foods and the Australian Guide to Healthy Eating are frequently used as nutritional assessment tools for menus in ‘well’ groups (such as boarding schools, prisons and mental health facilities), with the draft Foundation and Total Diets (FATD) the latest revision. The aim of this paper is to apply the FATD to an assessment of food provision in a long stay, ‘well’, group setting to determine its usefulness as a tool. A detailed menu review was conducted in a 1000 bed male prison, including verification of all recipes. Full diet histories were collected on 106 prisoners which included foods consumed from the menu and self funded snacks. Both the menu and diet histories were analysed according to core foods, with recipes used to assist in quantification of mixed dishes. Comparison was made of average core foods with Foundation Diet recommendations (FDR) for males. Results showed that the standard menu provided sufficient quantity for 8 of 13 FDRs, however was low in nuts, legumes, refined cereals and marginally low in fruits and orange vegetables. The average prisoner diet achieved 9 of 13 FDRs, notably with margarines and oils less than half and legumes one seventh of recommended. Overall, although the menu and prisoner diets could easily be assessed using the FDRs, it was not consistent with recommendations. In long stay settings other Nutrient Reference Values not modelled in the FATDS need consideration, in particular, Suggested Dietary Targets and professional judgement is required in interpretation.

Severity of driver injury and vehicle damage in traffic crashes at intersections: A Bayesian hierarchical analysis

Most crash severity studies ignored severity correlations between driver-vehicle units involved in the same crashes. Models without accounting for these within-crash correlations will result in biased estimates in the factor effects. This study developed a Bayesian hierarchical binomial logistic model to identify the significant factors affecting the severity level of driver injury and vehicle damage in traffic crashes at signalized intersections. Crash data in Singapore were employed to calibrate the model. Model fitness assessment and comparison using Intra-class Correlation Coefficient (ICC) and Deviance Information Criterion (DIC) ensured the suitability of introducing the crash-level random effects. Crashes occurring in peak time, in good street lighting condition, involving pedestrian injuries are associated with a lower severity, while those in night time, at T/Y type intersections, on right-most lane, and installed with red light camera have larger odds of being severe. Moreover, heavy vehicles have a better resistance on severe crash, while crashes involving two-wheel vehicles, young or aged drivers, and the involvement of offending party are more likely to result in severe injuries.

Applying Bayesian hierarchical models to examine motorcycle crashes at signalized intersections

Motorcycles are overrepresented in road traffic crashes and particularly vulnerable at signalized intersections. The objective of this study is to identify causal factors affecting the motorcycle crashes at both four-legged and T signalized intersections. Treating the data in time-series cross-section panels, this study explores different Hierarchical Poisson models and found that the model allowing autoregressive lag 1 dependent specification in the error term is the most suitable. Results show that the number of lanes at the four-legged signalized intersections significantly increases motorcycle crashes largely because of the higher exposure resulting from higher motorcycle accumulation at the stop line. Furthermore, the presence of a wide median and an uncontrolled left-turn lane at major roadways of four-legged intersections exacerbate this potential hazard. For T signalized intersections, the presence of exclusive right-turn lane at both major and minor roadways and an uncontrolled left-turn lane at major roadways of T intersections increases motorcycle crashes. Motorcycle crashes increase on high-speed roadways because they are more vulnerable and less likely to react in time during conflicts. The presence of red light cameras reduces motorcycle crashes significantly for both four-legged and T intersections. With the red-light camera, motorcycles are less exposed to conflicts because it is observed that they are more disciplined in queuing at the stop line and less likely to jump start at the start of green.

Bayesian hierarchical analysis on crash prediction models

Traditional crash prediction models, such as generalized linear regression models, are incapable of taking into account the multilevel data structure, which extensively exists in crash data. Disregarding the possible within-group correlations can lead to the production of models giving unreliable and biased estimates of unknowns. This study innovatively proposes a -level hierarchy, viz. (Geographic region level – Traffic site level – Traffic crash level – Driver-vehicle unit level – Vehicle-occupant level) Time level, to establish a general form of multilevel data structure in traffic safety analysis. To properly model the potential cross-group heterogeneity due to the multilevel data structure, a framework of Bayesian hierarchical models that explicitly specify multilevel structure and correctly yield parameter estimates is introduced and recommended. The proposed method is illustrated in an individual-severity analysis of intersection crashes using the Singapore crash records. This study proved the importance of accounting for the within-group correlations and demonstrated the flexibilities and effectiveness of the Bayesian hierarchical method in modeling multilevel structure of traffic crash data.

Hotspot Identification: A Full Bayesian Hierarchical Modeling Approach

This study proposes a full Bayes (FB) hierarchical modeling approach in traffic crash hotspot identification. The FB approach is able to account for all uncertainties associated with crash risk and various risk factors by estimating a posterior distribution of the site safety on which various ranking criteria could be based. Moreover, by use of hierarchical model specification, FB approach is able to flexibly take into account various heterogeneities of crash occurrence due to spatiotemporal effects on traffic safety. Using Singapore intersection crash data(1997-2006), an empirical evaluate was conducted to compare the proposed FB approach to the state-of-the-art approaches. Results show that the Bayesian hierarchical models with accommodation for site specific effect and serial correlation have better goodness-of-fit than non hierarchical models. Furthermore, all model-based approaches perform significantly better in safety ranking than the naive approach using raw crash count. The FB hierarchical models were found to significantly outperform the standard EB approach in correctly identifying hotspots.

The quantum inspired modelling of changing attitudes and self-organising societies

We utilise the well-developed quantum decision models known to the QI community to create a higher order social decision making model. A simple Agent Based Model (ABM) of a society of agents with changing attitudes towards a social issue is presented, where the private attitudes of individuals in the system are represented using a geometric structure inspired by quantum theory. We track the changing attitudes of the members of that society, and their resulting propensities to act, or not, in a given social context. A number of new issues surrounding this "scaling up" of quantum decision theories are discussed, as well as new directions and opportunities.

Modelling and analysis of the crush zone of a typical Australian passenger train

In this paper, a three-dimensional nonlinear rigid body model has been developed for the investigation of the crashworthiness of a passenger train using the multibody dynamics approach. This model refers to a typical design of passenger cars and train constructs commonly used in Australia. The high-energy and low-energy crush zones of the cars and the train constructs are assumed and the data are explicitly provided in the paper. The crash scenario is limited to the train colliding on to a fixed barrier symmetrically. The simulations of a single car show that this initial design is only applicable for the crash speed of 35 km/h or lower. For higher speeds (e.g. 140 km/h), the crush lengths or crush forces or both the crush zone elements will have to be enlarged. It is generally better to increase the crush length than the crush force in order to retain the low levels of the longitudinal deceleration of the passenger cars.

Towards determining soft tissue properties for modelling spine surgery : current progress and challenges

Current complication rates for adolescent scoliosis surgery necessitate the development of better surgical planning tools to improve outcomes. Here we present our approach to developing finite element models of the thoracolumbar spine for deformity surgery simulation, with patient-specific model anatomy based on low-dose pre-operative computed tomography scans. In a first step towards defining patient-specific tissue properties, an initial 'benchmark' set of properties were used to simulate a clinically performed pre-operative spinal flexibility assessment, the fulcrum bending radiograph. Clinical data for ten patients were compared with the simulated results for this assessment and in cases where these data differed by more than 10%, soft tissue properties for the costo-vertebral joint (CVJt) were altered to achieve better agreement. Results from these analyses showed that changing the CVJt stiffness resulted in acceptable agreement between clinical and simulated flexibility in two of the six cases. In light of these results and those of our previous studies in this area, it is suggested that spinal flexibility in the fulcrum bending test is not governed by any single soft tissue structure acting in isolation. More detailed biomechanical characterisation of the fulcrum bending test is required to provide better data for determination of patient-specific soft tissue properties.