An architecture for agent-enhanced network service provisioning through SLA negotiation

This paper focuses on two main areas. We first investigate various aspects of subscription and session Service Level Agreement (SLA) issues such as negotiating and setting up network services with Quality of Service (QoS) and pricing preferences. We then introduce an agent-enhanced service architecture that facilitates these services. A prototype system consisting of real-time agents that represent various network stakeholders was developed. A novel approach is presented where the agent system is allowed to communicate with a simulated network. This allows functional and dynamic behaviour of the network to be investigated under various agent-supported scenarios. This paper also highlights the effects of SLA negotiation and dynamic pricing in a competitive multi-operator networks environment.

Learning soft computing control strategies in a modular neural network architecture

Modelling and control of nonlinear dynamical systems is a challenging problem since the dynamics of such systems change over their parameter space. Conventional methodologies for designing nonlinear control laws, such as gain scheduling, are effective because the designer partitions the overall complex control into a number of simpler sub-tasks. This paper describes a new genetic algorithm based method for the design of a modular neural network (MNN) control architecture that learns such partitions of an overall complex control task. Here a chromosome represents both the structure and parameters of an individual neural network in the MNN controller and a hierarchical fuzzy approach is used to select the chromosomes required to accomplish a given control task. This new strategy is applied to the end-point tracking of a single-link flexible manipulator modelled from experimental data. Results show that the MNN controller is simple to design and produces superior performance compared to a single neural network (SNN) controller which is theoretically capable of achieving the desired trajectory. (C) 2003 Elsevier Ltd. All rights reserved.

Secondary prevention of cardiovascular disease in different primary healthcare systems with and without pay-for-performance

Objective: To compare baseline cardiovascular risk management between people recruited from two different healthcare systems, to a research trial of an intervention to optimize secondary prevention. Design: Cross-sectional study. Setting: General practices, randomly selected: 16 in Northern Ireland (NI) (UK NHS, ‘strong’ infrastructure); 32 in Republic of Ireland (RoI) (mixed healthcare economy, less infrastructure). Patients: 903 (mean age 67.5 years; 69.9% male); randomly selected, known coronary heart disease. Main outcome measures: Blood pressure, cholesterol, medications; validated questionnaires for diet (DINE), exercise (Godin), quality of life (SF12); healthcare usage. Results: More RoI than NI participants had systolic BP>140 mmHg (37% v 28%, p=0.01) and cholesterol >5mmol/l (24% v 17%, p=0.02): RoI mean systolic BP was higher (139 v 132 mm Hg). More RoI participants reported a high fibre intake (35% v 23%), higher levels of physical activity (62% v 44%), and better physical and mental health (SF12); they had more GP (5.6 v 4.4) and fewer nurse visits (1.6 v 2.1) in the previous year. Fewer in RoI (55% v 70%) were prescribed B blockers. Both groups’ ACE inhibitor (41%; 48%) prescribing was similar; high proportions were prescribed statins (84%; 85%) and aspirin (83%; 77%). Conclusions Blood pressure and cholesterol are better controlled among patients in a primary healthcare system with a ‘strong’ infrastructure supporting computerization and rewarding measured performance but this is not associated with healthier lifestyle or better quality of life. Further exploration of differences in professionals’ and patients’ engagement in secondary prevention in different healthcare systems is needed.