Linking contracts, processes and services: An event-driven approach

This paper addresses the problem of mapping business contract conditions onto the messages and rules that represent service interactions in a collaborative business process. We describe why this mapping is not straightforward by means of an example. We then consider a message-driven process language as a target for the mapping and use this mapping solution to discuss broad range of problems related to the mapping problem.

Advanced patient monitoring displays: Tools or continuous informing

We reviewed the use of advanced display technologies for monitoring in anesthesia. Researchers are investigating displays that integrate information and that, in some cases, also deliver the results continuously to the anesthesiologist. Integrated visual displays reveal higher-order properties of patient state and speed in responding to events, but their benefits under an intensely timeshared load is unknown. Head-mounted displays seem to shorten the time to respond to changes, but their impact on peripheral awareness and attention is unknown. Continuous auditory displays extending pulse oximetry seem to shorten response times and improve the ability to time-share other tasks, but their integration into the already noisy operative environment still needs to be tested. We reviewed the advantages and disadvantages of the three approaches, drawing on findings from other fields, such as aviation, to suggest outcomes where there are still no results for the anesthesia context. Proving that advanced patient monitoring displays improve patient outcomes is difficult, and a more realistic goal is probably to prove that such displays lead to better situational awareness, earlier responding, and less workload, all of which keep anesthesia practice away from the outer boundaries of safe operation.

A framework for extreme-event control in wastewater treatment

In this paper an approach to extreme event control in wastewater treatment plant operation by use of automatic supervisory control is discussed. The framework presented is based on the fact that different operational conditions manifest themselves as clusters in a multivariate measurement space. These clusters are identified and linked to specific and corresponding events by use of principal component analysis and fuzzy c-means clustering. A reduced system model is assigned to each type of extreme event and used to calculate appropriate local controller set points. In earlier work we have shown that this approach is applicable to wastewater treatment control using look-up tables to determine current set points. In this work we focus on the automatic determination of appropriate set points by use of steady state and dynamic predictions. The performance of a relatively simple steady-state supervisory controller is compared with that of a model predictive supervisory controller. Also, a look-up table approach is included in the comparison, as it provides a simple and robust alternative to the steady-state and model predictive controllers, The methodology is illustrated in a simulation study.

A framework for table driven testing of Java classes

With the advent of object-oriented languages and the portability of Java, the development and use of class libraries has become widespread. Effective class reuse depends on class reliability which in turn depends on thorough testing. This paper describes a class testing approach based on modeling each test case with a tuple and then generating large numbers of tuples to thoroughly cover an input space with many interesting combinations of values. The testing approach is supported by the Roast framework for the testing of Java classes. Roast provides automated tuple generation based on boundary values, unit operations that support driver standardization, and test case templates used for code generation. Roast produces thorough, compact test drivers with low development and maintenance cost. The framework and tool support are illustrated on a number of non-trivial classes, including a graphical user interface policy manager. Quantitative results are presented to substantiate the practicality and effectiveness of the approach. Copyright (C) 2002 John Wiley Sons, Ltd.

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

Event-related FMRI analysis with maximum correlation modelling

Functional magnetic resonance imaging (FMRI) analysis methods can be quite generally divided into hypothesis-driven and data-driven approaches. The former are utilised in the majority of FMRI studies, where a specific haemodynamic response is modelled utilising knowledge of event timing during the scan, and is tested against the data using a t test or a correlation analysis. These approaches often lack the flexibility to account for variability in haemodynamic response across subjects and brain regions which is of specific interest in high-temporal resolution event-related studies. Current data-driven approaches attempt to identify components of interest in the data, but currently do not utilise any physiological information for the discrimination of these components. Here we present a hypothesis-driven approach that is an extension of Friman's maximum correlation modelling method (Neurolmage 16, 454-464, 2002) specifically focused on discriminating the temporal characteristics of event-related haemodynamic activity. Test analyses, on both simulated and real event-related FMRI data, will be presented.

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.

Institutional governance systems and variations in national competitive advantage: An integrative framework

Creating competitive industries has become one of the key tasks of governments. Different adaptation outcomes in industries across nations cannot be accounted for fully simply by an emphasis on firm-level capabilities, market-driven policies, or state-level policies. We propose an integrative framework that draws on both the strategic management and political economy literature to explain variations in national industrial competitiveness.. We discuss differences with respect to institutional characteristics and capabilities, competitive outcomes, conditions of best fit, and who bears the cost of industry adaptation.

A Computational Framework for Institutional Agency

This paper provides a computational framework, based on Defeasible Logic, to capture some aspects of institutional agency. Our background is Kanger-Lindahl-P\"orn account of organised interaction, which describes this interaction within a multi-modal logical setting. This work focuses in particular on the notions of counts-as link and on those of attempt and of personal and direct action to realise states of affairs. We show how standard Defeasible Logic can be extended to represent these concepts: the resulting system preserves some basic properties commonly attributed to them. In addition, the framework enjoys nice computational properties, as it turns out that the extension of any theory can be computed in time linear to the size of the theory itself.

Elite athletes: Why does the 'fire' burn so brightly?

Background and Purpose: What drives some athletes to achieve at the highest level whilst other athletes fail to achieve their physical potential? Why does the ‘fire’ burn so brightly for some elite athletes and not for others? A good understanding of an athlete’s motivation is critical to a coach designing an appropriate motivational climate to realize an athlete’s physical talent. This paper examines the motivational processes of elite athletes within the framework of three major social-cognitive theories of motivation. Method: Participants were five male and five female elite track and field athletes from Australia who had finished in the top ten at either the Olympic Games and/or the World Championships in the last six years. Qualitative data were collected using semi-structured interviews. Results and Discussion: Inductive analyses revealed several major themes associated with the motivational processes of elite athletes: (a) they were highly driven by personal goals and achievement, (b) they had strong self-belief, and (c) track and field was central to their lives. The findings are discussed in light of recent social-cognitive theories of motivation, namely, self-determination theory, the hierarchical model of motivation, and achievement goal theory. Self-determined forms of motivation characterised the elite athletes in this study and, consistent with social-cognitive theories of motivation, it is suggested that goal accomplishment enhances perceptions of competence and consequently promotes self-determined forms of motivation.

Experimental study of the quantum driven pendulum and its classical analog in atom optics

We present experimental results for the dynamics of cold atoms in a far detuned amplitude-modulated optical standing wave. Phase-space resonances constitute distinct peaks in the atomic momentum distribution containing up to 65% of all atoms resulting from a mixed quantum chaotic phase space. We characterize the atomic behavior in classical and quantum regimes and we present the applicable quantum and classical theory, which we have developed and refined. We show experimental proof that the size and the position of the resonances in phase space can be controlled by varying several parameters, such as the modulation frequency, the scaled well depth, the modulation amplitude, and the scaled Planck’s constant of the system. We have found a surprising stability against amplitude noise. We present methods to accurately control the momentum of an ensemble of atoms using these phase-space resonances which could be used for efficient phase-space state preparation.