Physical access control administration using building information models

Physical access control systems play a central role in the protection of critical infrastructures, where both the provision of timely access and preserving the security of sensitive areas are paramount. In this paper we discuss the shortcomings of existing approaches to the administration of physical access control in complex environments. At the heart of the problem is the current dependency on human administrators to reason about the implications of the provision or the revocation of staff access to an area within these facilities. We demonstrate how utilising Building Information Models (BIMs) and the capabilities they provide, including 3D representation of a facility and path-finding can reduce possible intentional or accidental errors made by security administrators.

An investigation on the accuracy of regional ocean models through field trials

Recent efforts in mission planning for underwater vehicles have utilised predictive models to aid in navigation, optimal path planning and drive opportunistic sampling. Although these models provide information at a unprecedented resolutions and have proven to increase accuracy and effectiveness in multiple campaigns, most are deterministic in nature. Thus, predictions cannot be incorporated into probabilistic planning frameworks, nor do they provide any metric on the variance or confidence of the output variables. In this paper, we provide an initial investigation into determining the confidence of ocean model predictions based on the results of multiple field deployments of two autonomous underwater vehicles. For multiple missions conducted over a two-month period in 2011, we compare actual vehicle executions to simulations of the same missions through the Regional Ocean Modeling System in an ocean region off the coast of southern California. This comparison provides a qualitative analysis of the current velocity predictions for areas within the selected deployment region. Ultimately, we present a spatial heat-map of the correlation between the ocean model predictions and the actual mission executions. Knowing where the model provides unreliable predictions can be incorporated into planners to increase the utility and application of the deterministic estimations.

A sequential Monte Carlo approach to the sequential design for discriminating between rival continuous data models

Here we present a sequential Monte Carlo approach to Bayesian sequential design for the incorporation of model uncertainty. The methodology is demonstrated through the development and implementation of two model discrimination utilities; mutual information and total separation, but it can also be applied more generally if one has different experimental aims. A sequential Monte Carlo algorithm is run for each rival model (in parallel), and provides a convenient estimate of the marginal likelihood (of each model) given the data, which can be used for model comparison and in the evaluation of utility functions. A major benefit of this approach is that it requires very little problem specific tuning and is also computationally efficient when compared to full Markov chain Monte Carlo approaches. This research is motivated by applications in drug development and chemical engineering.

Moving beyond transition pedagogy: Maturity models and student engagement

Australian higher education institutions (HEIs) have entered a new phase of regulation and accreditation which includes performance-based funding relating to the participation and retention of students from social and cultural groups previously underrepresented in higher education. However, in addressing these priorities, it is critical that HEIs do not further disadvantage students from certain groups by identifying them for attention because of their social or cultural backgrounds, circumstances which are largely beyond the control of students. In response, many HEIs are focusing effort on university-wide approaches to enhancing the student experience because such approaches will enhance the engagement, success and retention of all students, and in doing so, particularly benefit those students who come from underrepresented groups. Measuring and benchmarking student experiences and engagement that arise from these efforts is well supported by extensive collections of student experience survey data. However no comparable instrument exists that measures the capability of institutions to influence and/or enhance student experiences where capability is an indication of how well an organisational process does what it is designed to do (Rosemann & de Bruin, 2005). This paper proposes that the concept of a maturity model (Marshall, 2010; Paulk, 1999) may be useful as a way of assessing the capability of HEIs to provide and implement student engagement, success and retention activities. We will describe the Student Engagement, Success and Retention Maturity Model (SESR-MM), (Clarke, Nelson & Stoodley, 2012; Nelson, Clarke & Stoodley, 2012) we are currently investigating. We will discuss if our research may address the current gap by facilitating the development of an SESR-MM instrument that aims (i) to enable institutions to assess the capability of their current student engagement and retention programs and strategies to influence and respond to student experiences within the institution; and (ii) to provide institutions with the opportunity to understand various practices across the sector with a view to further improving programs and practices relevant to their context. The first aim of our research is to extend the generational approach which has been useful in considering the evolutionary nature of the first year experience (FYE) (Wilson, 2009). Three generations have been identified and explored: First generation approaches that focus on co-curricular strategies (e.g. orientation and peer programs); Second generation approaches that focus on curriculum (e.g. pedagogy, curriculum design, and learning and teaching practice); and third generation approaches—also referred to as transition pedagogy—that focus on the production of an institution-wide integrated holistic intentional blend of curricular and co-curricular activities (Kift, Nelson & Clarke, 2010). The second aim of this research is to move beyond assessments of students’ experiences to focus on assessing institutional processes and their capability to influence student engagement. In essence, we propose to develop and use the maturity model concept to produce an instrument that will indicate the capability of HEIs to manage and improve student engagement, success and retention programs and strategies. References Australian Council for Educational Research. (n.d.). Australasian Survey of Student Engagement. Retrieved from http://www.acer.edu.au/research/ausse/background Clarke, J., Nelson, K., & Stoodley, I. (2012, July). The Maturity Model concept as framework for assessing the capability of higher education institutions to address student engagement, success and retention: New horizon or false dawn? A Nuts & Bolts presentation at the 15th International Conference on the First Year in Higher Education, “New Horizons,” Brisbane, Australia. Kift, S., Nelson, K., & Clarke, J. (2010) Transition pedagogy - a third generation approach to FYE: A case study of policy and practice for the higher education sector. The International Journal of the First Year in Higher Education, 1(1), pp. 1-20. Department of Education, Employment and Workplace Relations. (n.d.). The University Experience Survey. Advancing quality in higher education information sheet. Retrieved from http://www.deewr.gov.au/HigherEducation/Policy/Documents/University_Experience_Survey.pdf Marshall, S. (2010). A quality framework for continuous improvement of e-Learning: The e-Learning Maturity Model. Journal of Distance Education, 24(1), 143-166. Nelson, K., Clarke, J., & Stoodley, I. (2012). An exploration of the Maturity Model concept as a vehicle for higher education institutions to assess their capability to address student engagement. A work in progress. Submitted for publication. Paulk, M. (1999). Using the Software CMM with good judgment, ASQ Software Quality Professional, 1(3), 19-29. Wilson, K. (2009, June–July). The impact of institutional, programmatic and personal interventions on an effective and sustainable first-year student experience. Keynote address presented at the 12th Pacific Rim First Year in Higher Education Conference, “Preparing for Tomorrow Today: The First Year as Foundation,” Townsville, Australia. Retrieved from http://www.fyhe.com.au/past_papers/papers09/ppts/Keithia_Wilson_paper.pdf

Bayesian experimental design for models with intractable likelihoods

In this paper we present a methodology for designing experiments for efficiently estimating the parameters of models with computationally intractable likelihoods. The approach combines a commonly used methodology for robust experimental design, based on Markov chain Monte Carlo sampling, with approximate Bayesian computation (ABC) to ensure that no likelihood evaluations are required. The utility function considered for precise parameter estimation is based upon the precision of the ABC posterior distribution, which we form efficiently via the ABC rejection algorithm based on pre-computed model simulations. Our focus is on stochastic models and, in particular, we investigate the methodology for Markov process models of epidemics and macroparasite population evolution. The macroparasite example involves a multivariate process and we assess the loss of information from not observing all variables.

What is the role of design-led innovation and design-led prototyping in developing novel business models?

Recently, ‘business model’ and ‘business model innovation’ have gained substantial attention in management literature and practice. However, many firms lack the capability to develop a novel business model to capture the value from new technologies. Existing literature on business model innovation highlights the central role of ‘customer value’. Further, it suggests that firms need to experiment with different business models and engage in ‘trail-and-error’ learning when participating in business model innovation. Trial-and error processes and prototyping with tangible artifacts are a fundamental characteristic of design. This conceptual paper explores the role of design-led innovation in facilitating firms to conceive and prototype novel and meaningful business models. It provides a brief review of the conceptual discussion on business model innovation and highlights the opportunities for linking it with the research stream of design-led innovation. We propose design-led business model innovation as a future research area and highlight the role of design-led prototyping and new types of artifacts and prototypes play within it. We present six propositions in order to outline future research avenues.

Evaluation of the GHR car following model for traffic safety studies

Traffic safety studies mandate more than what existing micro-simulation models can offer as they postulate that every driver exhibits a safe behaviour. All the microscopic traffic simulation models are consisting of a car-following model and the Gazis–Herman–Rothery (GHR) car-following model is a widely used model. This paper highlights the limitations of the GHR car-following model capability to model longitudinal driving behaviour for safety study purposes. This study reviews and compares different version of the GHR model. To empower the GHR model on precise metrics reproduction a new set of car-following model parameters is offered to simulate unsafe vehicle conflicts. NGSIM vehicle trajectory data is used to evaluate the new model and short following headways and Time to Collision are employed to assess critical safety events within traffic flow. Risky events are extracted from available NGSIM data to evaluate the modified model against the generic versions of the GHR model. The results from simulation tests illustrate that the proposed model does predict the safety metrics better than the generic GHR model. Additionally it can potentially facilitate assessing and predicting traffic facilities’ safety using microscopic simulation. The new model can predict Near-miss rear-end crashes.

The effects of lane-changing on the immediate follower : anticipation, relaxation, and change in driver characteristics

This paper investigates the effects of lane-changing in driver behavior by measuring (i) the induced transient behavior and (ii) the change in driver characteristics, i.e., changes in driver response time and minimum spacing. We find that the transition largely consists of a pre-insertion transition and a relaxation process. These two processes are different but can be reasonably captured with a single model. The findings also suggest that lane-changing induces a regressive effect on driver characteristics: a timid driver (characterized by larger response time and minimum spacing) tends to become less timid and an aggressive driver less aggressive. We offer an extension to Newell’s car-following model to describe this regressive effect and verify it using vehicle trajectory data.

Microscopic traffic hysteresis in traffic oscillations : a behavioral perspective

This paper studies traffic hysteresis arising in traffic oscillations from a behavioral perspective. It is found that the occurrence and type of traffic hysteresis is closely correlated with driver behavior when experiencing traffic oscillations and with the time driver reaction begins relative to the starting deceleration wave. Statistical results suggest that driver behavior is different depending on its position along the oscillation. This suggests that different car-following models should be used inside the different stages of an oscillation in order to replicate realistic congestion features.

The benefits of tree-based models for stock selection

The identification of the primary drivers of stock returns has been of great interest to both financial practitioners and academics alike for many decades. Influenced by classical financial theories such as the CAPM (Sharp, 1964; Lintner, 1965) and APT (Ross, 1976), a linear relationship is conventionally assumed between company characteristics as derived from their financial accounts and forward returns. Whilst this assumption may be a fair approximation to the underlying structural relationship, it is often adopted for the purpose of convenience. It is actually quite rare that the assumptions of distributional normality and a linear relationship are explicitly assessed in advance even though this information would help to inform the appropriate choice of modelling technique. Non-linear models have nevertheless been applied successfully to the task of stock selection in the past (Sorensen et al, 2000). However, their take-up by the investment community has been limited despite the fact that researchers in other fields have found them to be a useful way to express knowledge and aid decision-making...

Pedigree-free animal models : the relatedness matrix reloaded

Animal models typically require a known genetic pedigree to estimate quantitative genetic parameters. Here we test whether animal models can alternatively be based on estimates of relatedness derived entirely from molecular marker data. Our case study is the morphology of a wild bird population, for which we report estimates of the genetic variance-covariance matrices (G) of six morphological traits using three methods: the traditional animal model; a molecular marker-based approach to estimate heritability based on Ritland's pairwise regression method; and a new approach using a molecular genealogy arranged in a relatedness matrix (R) to replace the pedigree in an animal model. Using the traditional animal model, we found significant genetic variance for all six traits and positive genetic covariance among traits. The pairwise regression method did not return reliable estimates of quantitative genetic parameters in this population, with estimates of genetic variance and covariance typically being very small or negative. In contrast, we found mixed evidence for the use of the pedigree-free animal model. Similar to the pairwise regression method, the pedigree-free approach performed poorly when the full-rank R matrix based on the molecular genealogy was employed. However, performance improved substantially when we reduced the dimensionality of the R matrix in order to maximize the signal to noise ratio. Using reduced-rank R matrices generated estimates of genetic variance that were much closer to those from the traditional model. Nevertheless, this method was less reliable at estimating covariances, which were often estimated to be negative. Taken together, these results suggest that pedigree-free animal models can recover quantitative genetic information, although the signal remains relatively weak. It remains to be determined whether this problem can be overcome by the use of a more powerful battery of molecular markers and improved methods for reconstructing genealogies.

Infertility, medical advice and treatment with fertility hormones and/or in vitro fertilisation: a population perspective from the Australian Longitudinal Study on Women's Health

OBJECTIVE: To identify the factors associated with infertility, seeking advice and treatment with fertility hormones and/or in vitro fertilisation (IVF) among a general population of women. METHODS: Participants in the Australian Longitudinal Study on Women's Health aged 28-33 years in 2006 had completed up to four mailed surveys over 10 years (n=9,145). Parsimonious multivariate logistic regression was used to identify the socio-demographic, biological (including reproductive histories), and behavioural factors associated with infertility, advice and hormonal/IVF treatment. RESULTS: For women who had tried to conceive or had been pregnant (n=5,936), 17% reported infertility. Among women with infertility (n=1031), 72% (n=728) sought advice but only 50% (n=356) used hormonal/IVF treatment. Women had higher odds of infertility when: they had never been pregnant (OR=7.2, 95% CI 5.6-9.1) or had a history of miscarriage (OR range=1.5-4.0) than those who had given birth (and never had a miscarriage or termination). CONCLUSION: Only one-third of women with infertility used hormonal and/or IVF treatment. Women with PCOS or endometriosis were the most proactive in having sought advice and used hormonal/IVF treatment. IMPLICATIONS: Raised awareness of age-related declining fertility is important for partnered women aged approximately 30 years to encourage pregnancy during their prime reproductive years and reduce the risk of infertility.

Towards an integration of the theory of planned behaviour and cognitive behavioural strategies : an example from a school-based injury prevention programme

Adolescent risk-taking behavior has potentially serious injury consequences and school-based behavior change programs provide potential for reducing such harm. A well-designed program is likely to be theory-based and ecologically valid however it is rare that the operationalisation process of theories is described. The aim of this paper is to outline how the Theory of Planned Behavior and Cognitive Behavioral Therapy informed intervention design in a school setting. Teacher interviews provided insights into strategies that might be implemented within the curriculum and provided detail used to operationalise theory constructs. Benefits and challenges in applying both theories are described with examples from an injury prevention program, Skills for Preventing Injury in Youth.

The relationship between drivers’ perceptions toward police speed enforcement and self-reported speeding behaviour

Exceeding the speed limit and driving too fast for the conditions are regularly cited as significant contributing factors in traffic crashes, particularly fatal and serious injury crashes. Despite an extensive body of research highlighting the relationship between increased vehicle speeds and crash risk and severity, speeding remains a pervasive behaviour on Australian roads. The development of effective countermeasures designed to reduce the prevalence of speeding behaviour requires that this behaviour is well understood. The primary aim of this program of research was to develop a better understanding of the influence of drivers’ perceptions and attitudes toward police speed enforcement on speeding behaviour. Study 1 employed focus group discussions with 39 licensed drivers to explore the influence of perceptions relating to specific characteristics of speed enforcement policies and practices on drivers’ attitudes towards speed enforcement. Three primary factors were identified as being most influential: site selection; visibility; and automaticity (i.e., whether the enforcement approach is automated/camera-based or manually operated). Perceptions regarding these enforcement characteristics were found to influence attitudes regarding the perceived legitimacy and transparency of speed enforcement. Moreover, misperceptions regarding speed enforcement policies and practices appeared to also have a substantial impact on attitudes toward speed enforcement, typically in a negative direction. These findings have important implications for road safety given that prior research has suggested that the effectiveness of speed enforcement approaches may be reduced if efforts are perceived by drivers as being illegitimate, such that they do little to encourage voluntary compliance. Study 1 also examined the impact of speed enforcement approaches varying in the degree of visibility and automaticity on self-reported willingness to comply with speed limits. These discussions suggested that all of the examined speed enforcement approaches (see Section 1.5 for more details) generally showed potential to reduce vehicle speeds and encourage compliance with posted speed limits. Nonetheless, participant responses suggested a greater willingness to comply with approaches operated in a highly visible manner, irrespective of the corresponding level of automaticity of the approach. While less visible approaches were typically associated with poorer rates of driver acceptance (e.g., perceived as “sneaky” and “unfair”), participants reported that such approaches would likely encourage long-term and network-wide impacts on their own speeding behaviour, as a function of the increased unpredictability of operations and increased direct (specific deterrence) and vicarious (general deterrence) experiences with punishment. Participants in Study 1 suggested that automated approaches, particularly when operated in a highly visible manner, do little to encourage compliance with speed limits except in the immediate vicinity of the enforcement location. While speed cameras have been criticised on such grounds in the past, such approaches can still have substantial road safety benefits if implemented in high-risk settings. Moreover, site-learning effects associated with automated approaches can also be argued to be a beneficial by-product of enforcement, such that behavioural modifications are achieved even in the absence of actual enforcement. Conversely, manually operated approaches were reported to be associated with more network-wide impacts on behaviour. In addition, the reported acceptance of such methods was high, due to the increased swiftness of punishment, ability for additional illegal driving behaviours to be policed and the salutary influence associated with increased face-to-face contact with authority. Study 2 involved a quantitative survey conducted with 718 licensed Queensland drivers from metropolitan and regional areas. The survey sought to further examine the influence of the visibility and automaticity of operations on self-reported likelihood and duration of compliance. Overall, the results from Study 2 corroborated those of Study 1. All examined approaches were again found to encourage compliance with speed limits, such that all approaches could be considered to be “effective”. Nonetheless, significantly greater self-reported likelihood and duration of compliance was associated with visibly operated approaches, irrespective of the corresponding automaticity of the approach. In addition, the impact of automaticity was influenced by visibility; such that significantly greater self-reported likelihood of compliance was associated with manually operated approaches, but only when they are operated in a less visible fashion. Conversely, manually operated approaches were associated with significantly greater durations of self-reported compliance, but only when they are operated in a highly visible manner. Taken together, the findings from Studies 1 and 2 suggest that enforcement efforts, irrespective of their visibility or automaticity, generally encourage compliance with speed limits. However, the duration of these effects on behaviour upon removal of the enforcement efforts remains questionable and represents an area where current speed enforcement practices could possibly be improved. Overall, it appears that identifying the optimal mix of enforcement operations, implementing them at a sufficient intensity and increasing the unpredictability of enforcement efforts (e.g., greater use of less visible approaches, random scheduling) are critical elements of success. Hierarchical multiple regression analyses were also performed in Study 2 to investigate the punishment-related and attitudinal constructs that influence self-reported frequency of speeding behaviour. The research was based on the theoretical framework of expanded deterrence theory, augmented with three particular attitudinal constructs. Specifically, previous research examining the influence of attitudes on speeding behaviour has typically focussed on attitudes toward speeding behaviour in general only. This research sought to more comprehensively explore the influence of attitudes by also individually measuring and analysing attitudes toward speed enforcement and attitudes toward the appropriateness of speed limits on speeding behaviour. Consistent with previous research, a number of classical and expanded deterrence theory variables were found to significantly predict self-reported frequency of speeding behaviour. Significantly greater speeding behaviour was typically reported by those participants who perceived punishment associated with speeding to be less certain, who reported more frequent use of punishment avoidance strategies and who reported greater direct experiences with punishment. A number of interesting differences in the significant predictors among males and females, as well as younger and older drivers, were reported. Specifically, classical deterrence theory variables appeared most influential on the speeding behaviour of males and younger drivers, while expanded deterrence theory constructs appeared more influential for females. These findings have important implications for the development and implementation of speeding countermeasures. Of the attitudinal factors, significantly greater self-reported frequency of speeding behaviour was reported among participants who held more favourable attitudes toward speeding and who perceived speed limits to be set inappropriately low. Disappointingly, attitudes toward speed enforcement were found to have little influence on reported speeding behaviour, over and above the other deterrence theory and attitudinal constructs. Indeed, the relationship between attitudes toward speed enforcement and self-reported speeding behaviour was completely accounted for by attitudes toward speeding. Nonetheless, the complexity of attitudes toward speed enforcement are not yet fully understood and future research should more comprehensively explore the measurement of this construct. Finally, given the wealth of evidence (both in general and emerging from this program of research) highlighting the association between punishment avoidance and speeding behaviour, Study 2 also sought to investigate the factors that influence the self-reported propensity to use punishment avoidance strategies. A standard multiple regression analysis was conducted for exploratory purposes only. The results revealed that punishment-related and attitudinal factors significantly predicted approximately one fifth of the variance in the dependent variable. The perceived ability to avoid punishment, vicarious punishment experience, vicarious punishment avoidance and attitudes toward speeding were all significant predictors. Future research should examine these relationships more thoroughly and identify additional influential factors. In summary, the current program of research has a number of implications for road safety and speed enforcement policy and practice decision-making. The research highlights a number of potential avenues for the improvement of public education regarding enforcement efforts and provides a number of insights into punishment avoidance behaviours. In addition, the research adds strength to the argument that enforcement approaches should not only demonstrate effectiveness in achieving key road safety objectives, such as reduced vehicle speeds and associated crashes, but also strive to be transparent and legitimate, such that voluntary compliance is encouraged. A number of potential strategies are discussed (e.g., point-to-point speed cameras, intelligent speed adaptation. The correct mix and intensity of enforcement approaches appears critical for achieving optimum effectiveness from enforcement efforts, as well as enhancements in the unpredictability of operations and swiftness of punishment. Achievement of these goals should increase both the general and specific deterrent effects associated with enforcement through an increased perceived risk of detection and a more balanced exposure to punishment and punishment avoidance experiences.

Preface to special issue on digital human modelling for vehicle design and manufacturing

The automotive industry has been the focus of digital human modeling (DHM) research and application for many years. In the highly competitive marketplace for personal transportation, the desire to improve the customer’s experience has driven extensive research in both the physical and cognitive interaction between the vehicle and its occupants. Human models provide vehicle designers with tools to view and analyze product interactions before the first prototypes are built, potentially improving the design while reducing cost and development time. The focus of DHM research and applications began with prediction and representation of static postures for purposes of driver workstation layout, including assessments of seat adjustment ranges and exterior vision. Now DHMs are used for seat design and assessment of driver reach and ingress/egress. DHMs and related simulation tools are expanding into the cognitive domain, with computational models of perception and motion, and into the dynamic domain with models of physical responses to ride and vibration. Moreover, DHMs are now widely used to analyze the ergonomics of vehicle assembly tasks. In this case, the analysis aims to determine whether workers can be expected to complete the tasks safely and with good quality. This preface provides a review of the literature to provide context for the nine new papers presented in this special issue.