Model-Driven safety evaluation with state-event-based component failure annotations

Over the past years, the paradigm of component-based software engineering has been established in the construction of complex mission-critical systems. Due to this trend, there is a practical need for techniques that evaluate critical properties (such as safety, reliability, availability or performance) of these systems. In this paper, we review several high-level techniques for the evaluation of safety properties for component-based systems and we propose a new evaluation model (State Event Fault Trees) that extends safety analysis towards a lower abstraction level. This model possesses a state-event semantics and strong encapsulation, which is especially useful for the evaluation of component-based software systems. Finally, we compare the techniques and give suggestions for their combined usage

Incremental model transformation for the evolution of model-driven systems

Model transformations are an integral part of model-driven development. Incremental updates are a key execution scenario for transformations in model-based systems, and are especially important for the evolution of such systems. This paper presents a strategy for the incremental maintenance of declarative, rule-based transformation executions. The strategy involves recording dependencies of the transformation execution on information from source models and from the transformation definition. Changes to the source models or the transformation itself can then be directly mapped to their effects on transformation execution, allowing changes to target models to be computed efficiently. This particular approach has many benefits. It supports changes to both source models and transformation definitions, it can be applied to incomplete transformation executions, and a priori knowledge of volatility can be used to further increase the efficiency of change propagation.

Model driven distribution of collaborative business processes

In this paper, we present a top down approach for integrated process modelling and distributed process execution. The integrated process model can be utilized for global monitoring and visualization and distributed process models for local execution. Our main focus in this paper is the presentation of the approach to support automatic generation and linking of distributed process models from an integrated process definition.

Verifying metamodel coverage of model transformations

Since the object management group (OMG) commenced its model driven architecture (MDA) initiative, there has been considerable activity proposing and building automatic model transformation systems to help implement the MDA concept. Much less attention has been given to the need to ensure that model transformations generate the intended results. This paper explores one aspect of validation and verification for MDA: coverage of the source and/or target metamodels by a set of model transformations. The paper defines the property of metamodel coverage and some corresponding algorithms. This property helps the user assess which parts of a source (or target) metamodel are referenced by a given model transformation set. Some results are presented from a prototype implementation that is built on the eclipse modeling framework (EMF).

Mass uptake study of the diffusion of water and SBF into poly(2-hydroxyethyl methacrylate-co-tetrahydrofurfuryI methacrylate) containing aspirin or vitamin B-12

The ingress of water and Kokubo simulated body fluid (SBF) into poly (2-hydroxyethyl methacrylate) (PHEMA), and its co-polymers with tetrahydrofurduryl methacrylate (THFMA), loaded with either one of two model drugs, vitamin 1312 or aspirin, was studied by mass uptake over the temperature range 298-318 K. The polymers were studied as cylinders and were loaded with either 5 wt% or 10 wt% of the drugs. From DSC studies it was observed that vitamin B-12 behaved as a physical cross-linker restricting chain segmental mobility, and so had a small anti-plasticisation effect on PHEMA and the co-polymers rich in HEMA, but almost no effect on the T-g of co-polymers rich in THFMA. On the other hand, aspirin exhibited a plasticising effect on PHEMA and the copolymers. All of the polymers were found to absorb water and SBF according to a Fickian diffusion mechanism. The polymers were all found to swell to a greater extent in SBF than in water, which was attributed to the presence of Tris buffer in the SBF. The sorptions of the two penetrants were found to follow Fickian kinetics in all cases and the diffusion coefficients at 310 K for SBF were found to be smaller than those for water, except for the polymers containing aspirin where the diffusion coefficients were higher than for the other systems. For example, for sorption into PHEMA the diffusion coefficient for water was 1.41 X 10(-11) m(2)/s and for SBF was 0.79 x 10-11 m(2)/s, but in the presence of 5 wt% aspirin the corresponding values were 1.27 x 10(-1)1 m(2)/s and 1.25 x 10(-11) m(2)/s, respectively. The corresponding values for PHEMA loaded with 5 wt% B-12 were 1.25 x 10(-11) m(2)/s and 0.74 x 10(-11) m(2)/s, respectively.

Introduction of routine outcome measures: staff reactions and issues for consideration

The aim of this study was to explore clinician reactions to (i) the introduction of routine outcome measures and (ii) the utility of outcomes data in clinical practice. Focus group discussions (n = 34) were conducted with mental health staff (n = 324) at approximately 8 months post implementation of routine outcome measures. A semi-structured interview schedule was used to collect data on two key issues; reactions to the introduction of outcome measures and factors influencing the utility of outcomes data in clinical practice. Data from the discussion groups were analysed using content analysis to isolate emerging themes. While the majority of participants endorsed the collection and utilization of outcomes data, many raised questions about the merits of the initiative. Ambivalence, competing work demands, lack of support from senior medical staff, questionable evidence to support the use of outcome measures, and fear of how outcomes data might be used emerged as key issues. At 8 months post implementation a significant number of clinical staff remained ambivalent about the benefits of outcome measurement and had not engaged in the process. The shift to a service model driven by outcomes and case-mix data will take time and resources to achieve. Implications for nursing staff are discussed.

MQL: A powerful extension to OCL for MOF queries

The Meta-Object Facility (MOF) provides a standardized framework for object-oriented models. An instance of a MOF model contains objects and links whose interfaces are entirely derived from that model. Information contained in these objects can be accessed directly, however, in order to realize the Model-Driven Architecture@trade; (MDA), we must have a mechanism for representing and evaluating structured queries on these instances. The MOF Query Language (MQL) is a language that extends the UML's Object Constraint Language (OCL) to provide more expressive power, such as higher-order queries, parametric polymorphism and argument polymorphism. Not only do these features allow more powerful queries, but they also encourage a greater degree of modularization and re-use, resulting in faster prototyping and facilitating automated integrity analysis. This paper presents an overview of the motivations for developing MQL and also discusses its abstract syntax, presented as a MOF model, and its semantics

Data-driven fuzzy analysis in quantitative mineral resource assessment

The integration of geo-information from multiple sources and of diverse nature in developing mineral favourability indexes (MFIs) is a well-known problem in mineral exploration and mineral resource assessment. Fuzzy set theory provides a convenient framework to combine and analyse qualitative and quantitative data independently of their source or characteristics. A novel, data-driven formulation for calculating MFIs based on fuzzy analysis is developed in this paper. Different geo-variables are considered fuzzy sets and their appropriate membership functions are defined and modelled. A new weighted average-type aggregation operator is then introduced to generate a new fuzzy set representing mineral favourability. The membership grades of the new fuzzy set are considered as the MFI. The weights for the aggregation operation combine the individual membership functions of the geo-variables, and are derived using information from training areas and L, regression. The technique is demonstrated in a case study of skarn tin deposits and is used to integrate geological, geochemical and magnetic data. The study area covers a total of 22.5 km(2) and is divided into 349 cells, which include nine control cells. Nine geo-variables are considered in this study. Depending on the nature of the various geo-variables, four different types of membership functions are used to model the fuzzy membership of the geo-variables involved. (C) 2002 Elsevier Science Ltd. All rights reserved.

Diagnostic goal driven modelling and simulation of multiscale process systems

A systematic goal-driven top-down modelling methodology is proposed that is capable of developing a multiscale model of a process system for given diagnostic purposes. The diagnostic goal-set and the symptoms are extracted from HAZOP analysis results, where the possible actions to be performed in a fault situation are also described. The multiscale dynamic model is realized in the form of a hierarchical coloured Petri net by using a novel substitution place-transition pair. Multiscale simulation that focuses automatically on the fault areas is used to predict the effect of the proposed preventive actions. The notions and procedures are illustrated on some simple case studies including a heat exchanger network and a more complex wet granulation process.