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.

Learning to play Pac-Man: An evolutionary, rule-based approach

Pac-Man is a well-known, real-time computer game that provides an interesting platform for research. We describe an initial approach to developing an artificial agent that replaces the human to play a simplified version of Pac-Man. The agent is specified as a simple finite state machine and ruleset. with parameters that control the probability of movement by the agent given the constraints of the maze at some instant of time. In contrast to previous approaches, the agent represents a dynamic strategy for playing Pac-Man, rather than a pre-programmed maze-solving method. The agent adaptively "learns" through the application of population-based incremental learning (PBIL) to adjust the agents' parameters. Experimental results are presented that give insight into some of the complexities of the game, as well as highlighting the limitations and difficulties of the representation of the agent.

A review of telemedicine and asthma

The literature contains a number of reports of early work involving telemedicine and chronic disease; however, there are comparatively few studies in asthma. Most of the telemedicine studies in asthma have investigated the use of remote monitoring of patients in the home, e.g. transmitting spirometry data via a telephone modem to a central server. The primary objective of these studies was to improve management. A secondary benefit was that patient adherence to prescribed treatment is also likely to be improved. Early results are encouraging; home monitoring in a randomized controlled trial in Japan significantly reduced the number of emergency room visits by patients with poorly controlled asthma. Other studies have described the cost-benefits of a specialist asthma nurse who can manage patients by telephone contact, as well as deliver asthma education. Many web-based systems are available for the general public or healthcare professionals to improve education in asthma, although their quality is highly variable. The work on telemedicine in asthma clearly shows that the technique holds promise in a number of areas. Unfortunately - as in telemedicine generally - most of the literature in patients with asthma refers to pilot trials and feasibility studies, with short-term outcomes. Large-scale, formal research trials are required to establish the cost effectiveness of telemedicine in asthma.

Making decisions with the future in mind: Developmental and comparative identification of mental time travel

Mechanisms that produce behavior which increase future survival chances provide an adaptive advantage. The flexibility of human behavior is at least partly the result of one such mechanism, our ability to travel mentally in time and entertain potential future scenarios. We can study mental time travel in children using language. Current results suggest that key developments occur between the ages of three to five. However, linguistic performance can be misleading as language itself is developing. We therefore advocate the use of methodologies that focus on future-oriented action. Mental time travel required profound changes in humans' motivational system, so that current behavior could be directed to secure not just present, but individually anticipated future needs. Such behavior should be distinguishable from behavior based on current drives, or on other mechanisms. We propose an experimental paradigm that provides subjects with an opportunity to act now to satisfy a need not currently experienced. This approach may be used to assess mental time travel in nonhuman animals. We conclude by describing a preliminary study employing an adaptation of this paradigm for children. (c) 2005 Elsevier Inc. All rights reserved.

Modelling pre-clearing vegetation distribution using GIS-integrated statistical, ecological and data models: A case study from the wet tropics of Northeastern Australia

Traditional vegetation mapping methods use high cost, labour-intensive aerial photography interpretation. This approach can be subjective and is limited by factors such as the extent of remnant vegetation, and the differing scale and quality of aerial photography over time. An alternative approach is proposed which integrates a data model, a statistical model and an ecological model using sophisticated Geographic Information Systems (GIS) techniques and rule-based systems to support fine-scale vegetation community modelling. This approach is based on a more realistic representation of vegetation patterns with transitional gradients from one vegetation community to another. Arbitrary, though often unrealistic, sharp boundaries can be imposed on the model by the application of statistical methods. This GIS-integrated multivariate approach is applied to the problem of vegetation mapping in the complex vegetation communities of the Innisfail Lowlands in the Wet Tropics bioregion of Northeastern Australia. The paper presents the full cycle of this vegetation modelling approach including sampling sites, variable selection, model selection, model implementation, internal model assessment, model prediction assessments, models integration of discrete vegetation community models to generate a composite pre-clearing vegetation map, independent data set model validation and model prediction's scale assessments. An accurate pre-clearing vegetation map of the Innisfail Lowlands was generated (0.83r(2)) through GIS integration of 28 separate statistical models. This modelling approach has good potential for wider application, including provision of. vital information for conservation planning and management; a scientific basis for rehabilitation of disturbed and cleared areas; a viable method for the production of adequate vegetation maps for conservation and forestry planning of poorly-studied areas. (c) 2006 Elsevier B.V. All rights reserved.

An automated failure mode and effect analysis based on high-level design specificication with behavior trees

Formal methods have significant benefits for developing safety critical systems, in that they allow for correctness proofs, model checking safety and liveness properties, deadlock checking, etc. However, formal methods do not scale very well and demand specialist skills, when developing real-world systems. For these reasons, development and analysis of large-scale safety critical systems will require effective integration of formal and informal methods. In this paper, we use such an integrative approach to automate Failure Modes and Effects Analysis (FMEA), a widely used system safety analysis technique, using a high-level graphical modelling notation (Behavior Trees) and model checking. We inject component failure modes into the Behavior Trees and translate the resulting Behavior Trees to SAL code. This enables us to model check if the system in the presence of these faults satisfies its safety properties, specified by temporal logic formulas. The benefit of this process is tool support that automates the tedious and error-prone aspects of FMEA.