Titlebook: Advances in Intelligent Data Analysis IX; 9th International Sy Paul R. Cohen,Niall M. Adams,Michael R. Berthold Conference proceedings 2010

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K. GowriSankaran,J. Bliedtner,I. Netukaterms of data capture, management, analysis and reporting. The project is concerned with the intelligent monitoring and analysis of large infrastructural projects in the public domain, such as public roads, highways, tunnels and bridges. As a demonstrator, the project includes the detailed measureme

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Dialogical Justice in World Affairs,utomata (DFA) and Knowledge Discovery in Data Mining (KDD) TV-Tree. Mining EEG patterns in human brain dynamics is complex yet necessary for identifying and predicting the transient events that occur before and during epileptic seizures. We believe that an intelligent data analysis of mining EEG Epi

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Quantum query algorithms and lower bounds, present a general framework for automatic extraction, characterisation and classification of fMRI images, based on their functional properties. The proposed method identifies the section of each of those images, by morphological processing, and estimates the coordinates of the brain activated regio

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,Fundamentals of?Symmetric Key Cryptography,roblem of determining which class of kernels should be used in a geometric framework for nearest neighbor-based outlier detection. It introduces the class of similarity kernels and employs it within that framework. We also propose the use of isotropic stationary kernels for the case of normed input

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,Fundamentals of?Symmetric Key Cryptography,ing, a domain that is fraught with difficult automation issues. First, experts must work with a huge array of possible parameters. Our system ACE handles this issue by pushing the bounds of software flexibility. Furthermore, isotope dating experts reason about groups of samples using a large number

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Information Retrieval from Black Holesproach to agriculture, which is strongly connected with a number of data mining problems. One of those is also an inherently important task in agriculture: yield prediction. Given a yield prediction model, which of the predictor variables are the important ones?.In the past, a number of approaches h