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Titlebook: Artificial Intelligence and Innovations 2007: From Theory to Applications; Proceedings of the 4 Christos Boukis,Aristodemos Pnevmatikakis,L

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Patient Fall Detection using Support Vector Machinest. Sensors equipped with accelerometers are attached on the body of the patients and transmit patient movement data wirelessly to the monitoring unit. The methodology of support Vector Machines is used for precise classification of the acquired data and determination of a fall emergency event. Then
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Service Decomposition and Task Allocation in Distributed Computing Environmentsrvice logic deployment and current system & network load conditions. The pertinent problem is concisely defined, mathematically formulated, optimally solved and evaluated through simulation experiments.
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Conference proceedings 2007machine learning whose concern is the development of algorithms and techniques that allow computers to learn. The purpose of the 4th IFIP Conference on Artificial Intelligence Applications and Innovations (AIAI) is to bring together researchers, engineers and practitioners interested in the technica
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Artificial Intelligence and Innovations 2007: From Theory to ApplicationsProceedings of the 4
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https://doi.org/10.1007/978-981-97-6087-9ined as a secondary classifier pool, and an instance from the latent set replaces the currently active classifier whenever certain criteria are met. We discuss motivation behind this architecture, algorithmic details and future directions for this research.
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