Purposeful program theory: Effective use of theories of change and logic models [Book Review]

The purpose of this book by two Australian authors is to: introduce the audience to the full complement of contextual elements found within program theory; offer practical suggestions to engage with theories of change, theories of action and logic models; and provide substantial evidence for this approach through scholarly literature, practice case studies together with the authors' combined experience of 60 years.

A policy model for access control using building information models

Building information models have created a paradigm shift in how buildings are built and managed by providing a dynamic repository for building data that is useful in many new operational scenarios. This change has also created an opportunity to use building information models as an integral part of security operations and especially as a tool to facilitate fine-grained access control to building spaces in smart buildings and critical infrastructure environments. In this paper, we identify the requirements for a security policy model for such an access control system and discuss why the existing policy models are not suitable for this application. We propose a new policy language extension to XACML, with BIM specific data types and functions based on the IFC specification, which we call BIM-XACML.

Graph theory based representation of building information models for access control applications

Building information models are increasingly being utilised for facility management of large facilities such as critical infrastructures. In such environments, it is valuable to utilise the vast amount of data contained within the building information models to improve access control administration. The use of building information models in access control scenarios can provide 3D visualisation of buildings as well as many other advantages such as automation of essential tasks including path finding, consistency detection, and accessibility verification. However, there is no mathematical model for building information models that can be used to describe and compute these functions. In this paper, we show how graph theory can be utilised as a representation language of building information models and the proposed security related functions. This graph-theoretic representation allows for mathematically representing building information models and performing computations using these functions.

A pseudo-marginal sequential Monte Carlo algorithm for random effects models in Bayesian sequential design

A computationally efficient sequential Monte Carlo algorithm is proposed for the sequential design of experiments for the collection of block data described by mixed effects models. The difficulty in applying a sequential Monte Carlo algorithm in such settings is the need to evaluate the observed data likelihood, which is typically intractable for all but linear Gaussian models. To overcome this difficulty, we propose to unbiasedly estimate the likelihood, and perform inference and make decisions based on an exact-approximate algorithm. Two estimates are proposed: using Quasi Monte Carlo methods and using the Laplace approximation with importance sampling. Both of these approaches can be computationally expensive, so we propose exploiting parallel computational architectures to ensure designs can be derived in a timely manner. We also extend our approach to allow for model uncertainty. This research is motivated by important pharmacological studies related to the treatment of critically ill patients.

Keeping our nursing and midwifery workforce : factors that support non-practising clinicians to return to practice

BACKGROUND: Within Australia and internationally (Health Workforce Australia, 2012) an increasing and on-going nursing workforce shortage is documented. Recent international estimates indicate that there will be ongoing and significant gaps in the supply of a nursing workforce; the United Kingdom is predicted to have a reduction of 12.12% nurses over the coming eight years if a current 'steady state' is maintained (Buchan and Seacombe, 2011); Canada is predicted to have a shortage of 60,000 nurses by 2022 (Tomblin et al., 2012) with Australia's anticipated nursing shortage reported as over 90,000 by the year 2025 (Health Workforce Australia, 2012). Queensland Health in response to their tracked emerging nursing and midwifery workforce shortages developed a nursing and midwifery refresher programme to return registered staff back to the workforce. A study was undertaken between 2008 and 2010 to provide an understanding of how non-practising nurses and midwives maybe supported back into the workforce. METHODS: Programme applicants (444) were invited to respond to an on-line survey designed to understand what aspects of the programme supported their learning and ability to return to the workforce. This number represents those who applied but not all completed or commenced the programme. Descriptive statistics (Polit and Beck, 2008) were used to collate quantifiable survey responses and free text and unsolicited responses were themed. RESULTS: The survey received a 35.5% response rate (n=158) with a return of 20% of unsolicited comments in the form of e-mail responses which were included in the themed results. Key themes supporting participants' learning and ability to return to the workforce were: Respondents were 94% female and 6% male, with 37.7% >51 years of age. Child rearing was the foremost reason for female staff relinquishing workforce roles (36.6%). The primary reason for returning to the workforce was maintenance of registration (40.5%). Both theory and clinical placement components were seen by participants as contributing to their confidence to return to the health workforce. CONCLUSION: The Queensland Nursing and Midwifery Refresher Programs provided a structured programme for registered, non-practising nurses and midwives to return to the Queensland Health workforce. Responses indicated that clinical supervision and contract learning should be central to a return to workforce induction programme for registered but non-practising nurses and midwives. The majority of nurses and midwives returning to the workforce were approaching retirement age in 10-15 years.

Incorporating human-factors in car-following models : a review of recent developments and research needs

Over the past decades there has been a considerable development in the modeling of car-following (CF) behavior as a result of research undertaken by both traffic engineers and traffic psychologists. While traffic engineers seek to understand the behavior of a traffic stream, traffic psychologists seek to describe the human abilities and errors involved in the driving process. This paper provides a comprehensive review of these two research streams. It is necessary to consider human-factors in {CF} modeling for a more realistic representation of {CF} behavior in complex driving situations (for example, in traffic breakdowns, crash-prone situations, and adverse weather conditions) to improve traffic safety and to better understand widely-reported puzzling traffic flow phenomena, such as capacity drop, stop-and-go oscillations, and traffic hysteresis. While there are some excellent reviews of {CF} models available in the literature, none of these specifically focuses on the human factors in these models. This paper addresses this gap by reviewing the available literature with a specific focus on the latest advances in car-following models from both the engineering and human behavior points of view. In so doing, it analyses the benefits and limitations of various models and highlights future research needs in the area.

Theorizing the use of multiple conceptual models in combination

Conceptual modelling continues to be an important means for graphically capturing the requirements of an information system. Observations of modelling practice suggest that modellers often use multiple conceptual models in combination, because they articulate different aspects of real-world domains. Yet, the available empirical as well as theoretical research in this area has largely studied the use of single models, or single modelling grammars. We develop a Theory of Combined Ontological Coverage by extending an existing theory of ontological expressiveness of conceptual modelling grammars. Our new theory posits that multiple conceptual models are used to increase the maximum coverage of the real-world domain being modelled, whilst trying to minimize the ontological overlap between the models. We illustrate how the theory can be applied to analyse sets of conceptual models. We develop three propositions of the theory about evaluations of model combinations in terms of users’ selection, understandability and usefulness of conceptual models.