978 resultados para Integrable spin chains (vertex models)


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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.

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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.

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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.

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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.

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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.

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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.

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In this paper new online adaptive hidden Markov model (HMM) state estimation schemes are developed, based on extended least squares (ELS) concepts and recursive prediction error (RPE) methods. The best of the new schemes exploit the idempotent nature of Markov chains and work with a least squares prediction error index, using a posterior estimates, more suited to Markov models then traditionally used in identification of linear systems.

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This paper develops maximum likelihood (ML) estimation schemes for finite-state semi-Markov chains in white Gaussian noise. We assume that the semi-Markov chain is characterised by transition probabilities of known parametric from with unknown parameters. We reformulate this hidden semi-Markov model (HSM) problem in the scalar case as a two-vector homogeneous hidden Markov model (HMM) problem in which the state consist of the signal augmented by the time to last transition. With this reformulation we apply the expectation Maximumisation (EM ) algorithm to obtain ML estimates of the transition probabilities parameters, Markov state levels and noise variance. To demonstrate our proposed schemes, motivated by neuro-biological applications, we use a damped sinusoidal parameterised function for the transition probabilities.

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The fragmentation of previously integrated systems of production and service delivery has been an important feature of organisational restructuring over the last three decades. This article highlights the adverse implications of this development for the health and safety of workers, examines the extent to which current British health and safety law provides an adequate framework for addressing these outcomes and explores whether its capacity to do so could be enhanced through the introduction of new statutory provisions on the regulation of supply chains. It concludes that, in terms of both structure and operation, the present framework of law is problematic. It further argues that recent international initiatives show that it is feasible to develop such statutory provisions and that existing evidence suggests that provisions of this type could usefully be introduced in respect of a number of areas of activity where the implications of the externalisation of production and service delivery seem particularly problematic.

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Over the past 20 years the labour market, workforce and work organisation of most if not all industrialised countries have been significantly refashioned by the increased use of more flexible work arrangements, variously labelled as precarious employment or contingent work. There is now a substantial and growing body of international evidence that many of these arrangements are associated with a significant deterioration in occupational health and safety (OHS), using a range of measures such as injury rates, disease, hazard exposures and work-related stress. Moreover, there is an emerging body of evidence that these arrangements pose particular problems for conventional regulatory regimes. Recognition of these problems has aroused the concern of policy makers - especially in Europe, North America and Australia - and a number of responses have been adopted in terms of modifying legislation, producing new guidance material and codes of practice and revised enforcement practices. This article describes one such in itiative in Australia with regard to home-based clothing workers. The regulatory strategy developed in one Australian jurisdiction (and now being ‘exported’ into others) seeks to counter this process via contractual tracking mechanisms to follow the work, tie in liability and shift overarching legal responsibility to the top of the supply chain. The process also entails the integration of minimum standards relating to wages, hours and working conditions; OHS and access to workers’ compensation. While home-based clothing manufacture represents a very old type of ‘flexible’ work arrangement, it is one that regulators have found especially difficult to address. Further, the elaborate multi-tiered subcont racting and diffuse work locations found in this industry are also characteristic of newer forms of contingent work in other industries (such as some telework) and the regulatory challenges they pose (such as the tendency of elaborate supply chains to attenuate and fracture statutory responsibilities, at least in terms of the attitudes and behaviour of those involved).