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We present an attempt to separate between two kinds of events, using Genetic Algorithms. Events were produced by a Monte Carlo generator and characterized by the most discriminant variables. For the separation between events, two approaches are investigated. First, discriminant function parameters and neural network connection weights are optimized. In a multidimensional search approach, hyper-planes...
In this work the convergence of ICT security and physical security is addressed. Starting by analyzing the impact of technology penetration on the global market and subsequently on security. Security spending in the Global IT market is analyzed, focusing on the development of the split out, which revealed the fact that spending is not always in the right sector. ICT Security and its classification...
Machine learning has become the predominant problem-solving strategy for computational linguistics problems in the last decade. In this paper, we present an implemented machine learning system for the automatic identification of non-referential pronouns in Arabic texts. Our system is based on a Bayesian network which has shown its efficiency for modeling NLP problems. We have evaluated our approach...
In the field of pattern recognition multiple classifier systems based on the combination of outputs from different classifiers have been proposed as a method of high performance classification systems. The objective of this work is to develop a fuzzy Gaussian classifier for combining multiple learners, we use a fuzzy Gaussian model to combine the outputs obtained from K-nearest neighbor classifier...
Mammography is the most effective and available tool for breast cancer screening. However, the low positive predictive value of breast biopsy resulting from mammogram interpretation leads to approximately 70% unnecessary biopsies with benign outcomes. Data mining algorithms could be used to help physicians in their decisions to perform a breast biopsy on a suspicious lesion seen in a mammogram image...
While there is an increasing need to share medical information for public health research, such data sharing must preserve patient privacy without disclosing any information that can be used to identify a patient. A considerable amount of research in data privacy community has been devoted to formalizing the notion of identifiability and developing techniques for anonymization but are focused exclusively...
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