in this paper, an object-based, highly scalable, lossy-to-lossless 3d wavelet coding approach for volumetric medical image data (e.g. mr and ct) is proposed. the new method, called 3dobhs-spiht, is based on the well known set partitioning in hierarchical trees (spiht) algorithm and supports both quality and resolution scalability. the 3d input data is grouped into groups of slices (gos) and eac...

Much work has studied the e¤ect of di¤erent treatments of missing values on model induction, but little work has analyzed treatments for the common case of missing values at prediction time. This paper …rst compares several di¤erent methods— predictive value imputation, the distribution-based imputation used by C4.5, and using reduced models— for applying classi…cation trees to instances with m...

Medical images show a great interest since it is needed in various medical applications. In order to decrease the size of medical images which are needed to be transmitted in a faster way; Region of Interest (ROI) and hybrid lossless compression techniques are applied on medical images to be compressed without losing important data. In this paper, a proposed model will be presented and assessed...

in this paper a novel fuzzy scheme for medical x-ray image classification is presented. in this method, any image is partitioned in to 25 overlapping subimages and then shape-texture features are extracted from shape and directional information extracted from any subimage. in the classification stage, we apply a fuzzy membership to any subimage with respect to euclidean distance between feature...

This article is a report concerning the two years of the XML Mining track at INEX (2005 and 2006). We focus here on the classication and clustering of XML documents. We detail these two tasks and the corpus used for this challenge and then present a summary of the di erent methods proposed by the participants. We last compare the results obtained during the two years of the track.

In this article, we consider the inverse Galois problem for parameterized differential equations over k((t))(x) with k any field of characteristic zero and use the method of patching over fields due to Harbater and Hartmann. As an application, we prove that every connected semisimple k((t))-split linear algebraic group is a parameterized Galois group over k((t))(x). 2010 Mathematics Subject Cla...

In this article, we review unsupervised neural network learning procedures which can be applied to the task of preprocessing raw data to extract useful features for subsequent classication. The learning algorithms reviewed here are grouped into three sections: informationpreserving methods, density estimation methods, and feature extraction methods. Each of these major sections concludes with a...

Vulnerability discovery and exploits detection are two wide areas of study in software engineering. This preliminary work tries to combine existing methods with machine learning techniques to define a metric classification of vulnerable computer programs. First a feature set has been defined and later two models have been tested against real world vulnerabilities. A relation between the classif...