Paul Moynihan

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Five different algorithms for determining left ventricular (LV) ejection fraction (EF) and volumes from two-dimensional echocardiographic examination (TDE) were compared with standard methods for obtaining EF and volume from x-ray cineangiography (cine) and EF from radionuclide ventriculography (RVG) in 35 patients. Although all methods correlated(More)
Different approaches to the quantification of regional left ventricular (LV) function from two-dimensional echocardiographic (2-D echo) images were assessed for their ability to optimize interobserver reproducibility in a heterogeneous patient population and to minimize the variability of regional function observed in a homogeneous normal population. Areas,(More)
SUMMARY The quantitative approaches to the assessment of regional left ventricular (LV) function described in the preceding paper were applied in a well-defined population of patients with coronary artery disease. Two groups were chosen by electrocardiographic and angiographic criteria: group 1 had infarction and regional wall motion abnormalities and group(More)
The paper describes a service oriented knowledge-based architecture to support supply chain application. The proposed architecture has the capability to meet the on- demand requirements of dynamic supply chains. Business requirements and potential benefits associated with our solution have been discussed. The research has led to an intelligent SOA(More)
In this paper, we introduce a service framework for supply chain management, which runs on a heterogeneous network and leverages the power of an inference engine to manage networks and supply chain entities. Details of design and implementation of the framework are given along with the discussions on the preliminary experimental results and impacts for(More)
In this paper, we introduce a service framework for supply chain management, this is a top level rule based design, it can handle heterogeneous networks and allows integration with key enabling technologies like RFID tracking and leverages the power of an inference engine to manage, monitor and optimize flow networks and supply chain entities. An extension(More)
In this paper, we introduce a real time process modeling framework for supply chains. The superior feature of this framework is that it draws a dynamically packaged process utilizing the existing available resources and supporting activities for supply chain management. The paper presents a top level rule based design that can handle heterogeneous networks(More)
A de-regulated supply chain network allows providers and requesters to freely engage with each other without having to go through the pre-agreed supply chain channels. This poses a potentially complex situation with a high degree of uncertainty in an e-business environment where the size of the marketplace can grow very rapidly. Inference is a way of(More)
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