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.

Genetic susceptibility to environmental toxicants : the interface between human and experimental studies in the development of new toxicological concepts

The growing knowledge of the genetic polymorphisms of enzymes metabolising xenobiotics in humans and their connections with individual susceptibility towards toxicants has created new and important interfaces between human epidemiology and experimental toxicology. The results of molecular epidemiological studies may provide new hypotheses and concepts, which call for experimental verification, and experimental concepts may obtain further proof by molecular epidemiological studies. If applied diligently, these possibilities may be combined to lead to new strategies of human-oriented toxicological research. This overview will present some outstanding examples for such strategies taken from the practically very important field of occupational toxicology. The main focus is placed on the effects of enzyme polymorphisms of the xenobiotic metabolism in association with the induction of bladder cancer and renal cell cancer after exposure to occupational chemicals. Also, smoking and induction of head and neck squamous cell cancer are considered.

Interface of graphane with copper : a van der Waals density-functional study

Various forms of hydrogenated graphene have been produced to date by several groups, while the synthesis of pure graphane has not been achieved yet. The study of the interface between graphane, in all its possible hydrogenation configurations, and catalyst metal surfaces can be pivotal to assess the feasibility of direct CVD growth methods for this material. We investigated the adhesion of graphane to a Cu(111) surface by adopting the vdW-DF2-C09 exchange-correlation functional, which is able to describe dispersion forces. The results are further compared with the PBE and the LDA exchange-correlation functionals. We calculated the most stable geometrical configurations of the slab/graphane interface and evaluated how graphane's geometrical parameters are modified. We show that dispersion forces play an important role in the slab/graphane adhesion. Band structure calculations demonstrated that in the presence of the interaction with copper, the band gap of graphane is not only preserved, but also enlarged, and this increase can be attributed to the electronic charge accumulated at the interface. We calculated a substantial energy barrier at the interface, suggesting that CVD graphane films might act as reliable and stable insulating thin coatings, or also be used to form compound layers in conjunction with metals and semiconductors.

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.

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.

Including nonequilibrium interface kinetics in a continuum model for melting nanoscaled particles

The melting temperature of a nanoscaled particle is known to decrease as the curvature of the solid-melt interface increases. This relationship is most often modelled by a Gibbs--Thomson law, with the decrease in melting temperature proposed to be a product of the curvature of the solid-melt interface and the surface tension. Such a law must break down for sufficiently small particles, since the curvature becomes singular in the limit that the particle radius vanishes. Furthermore, the use of this law as a boundary condition for a Stefan-type continuum model is problematic because it leads to a physically unrealistic form of mathematical blow-up at a finite particle radius. By numerical simulation, we show that the inclusion of nonequilibrium interface kinetics in the Gibbs--Thomson law regularises the continuum model, so that the mathematical blow up is suppressed. As a result, the solution continues until complete melting, and the corresponding melting temperature remains finite for all time. The results of the adjusted model are consistent with experimental findings of abrupt melting of nanoscaled particles. This small-particle regime appears to be closely related to the problem of melting a superheated particle.

Tales of science and defiance : the case for co-learning and collaboration in bridging the science/emotion divide in water recycling debates

Although science is generally assumed to be well integrated into rational decision-making models, it can be used to destabilise consultative processes, particularly when emotions are involved. Water policies are often seen as debates over technical and engineering issues, but can be highly controversial. Recycled water proposals, in particular, can create highly emotive conflicts. Through a case study regarding the rejection of recycled water proposals in the south-east Queensland, Australia, we explore the influence of science and emotions in contemporary water planning. We highlight the dangers inherent in promoting technical water planning issues at the expense of appropriate consideration of citizen concerns. Combining the science–policy interface and stakeholder engagement literatures, we advocate for collaborative decision-making processes that accommodate emotions and value judgements. A more collaborative stakeholder engagement model, founded on the principles of co-learning, has the potential to broaden the decision-making base and to promote better and more inclusive decision-making.

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.