This paper describes the design, development and clinical trials completed on an ambulatory, wireless ECG / vital signs monitor, which was designed to work on standard wireless LAN networking systems (802.11b). It discusses the trials, results collected from two prototype sensor devices, the limitations of the system in place due to architecture and site location. Future works identified from the clinical trials completed will also be discussed.

Semantic Web technologies are bring increasingly employed to solve knowledge management issues in traditional Web technologies. This paper follows that trend and proposes using Semantic rule languages to construct rules for defining access control rules for Web Services. Using these rules, a system will be able to manage access to Web Services and also the information accessed via these services.

This paper outlines a system for detection of cardiac arrhythmias within ECG signals, based on a Bayesian artificial neural network (ANN) classifier. The Bayesian (or probabilistic) ANN classifier is built by the use of a logistic regression model and the backpropagation algorithm based on a Bayesian framework. Its performance for this task is evaluated by comparison with other classifiers including Naive Bayes, decision trees, logistic regression, and RBF networks. A paired t-test is employed in comparing classifiers to select the optimum model. The system is evaluated using noisy ECG data, to simulate a real-world environment. It is hoped that the system can be further developed and fine-tuned for practical application.

We consider a dynamic market-place of self-interested agents with differing capabilities. A task to be completed is proposed to the agent population. An agent attempts to form a coalition of agents to perform the task. Before proposing a coalition, the agent must determine the optimal set of agents with whom to enter into a coalition for this task; we refer to this activity as coalition calculation. To determine the optimal coalition, the agent must have a means of calculating the value of any given coalition. Multiple metrics (cost, time, quality etc.) determine the true value of a coalition. However, because of conflicting metrics, differing metric importance and the tendency of metric importance to vary over time, it is difficult to obtain a true valuation of a given coalition. Previous work has not addressed these issues. We present a solution based on the adaptation of a multi-objective optimization evolutionary algorithm. In order to obtain a true valuation of any coalition, we use the concept of Pareto dominance coupled with a distance weighting algorithm. We determine the Pareto optimal set of coalitions and then use an instance-based learning algorithm to select the optimal coalition. We show through empirical evaluation that the proposed technique is capable of eliciting metric importance and adapting to metric variation over time.

This paper describes a number of enhancements for the standard CORBA Event Service. The basic service definition has been extended to support stream events, multimedia data flows, event fragmentation, quality of service definition, as well as multicast event delivery. The paper evaluates the service performance and describes experiences using the enhanced service in the development of a test application.