Behavioral axioms about preference orderings among gambles and their joint receipt lead to numerical representations consisting of a subjective utility term plus a term depending upon the events and the subjective weights. The results here are for uncertain alternatives, in much the same sense as Savage’s usage. Several open problems are described. Results for the risky case are in a second art...

Text reuse is common in many scenarios and documents are often based, at least in part, on existing documents. This paper reports an approach to detecting text reuse which identifies not only documents which have been reused verbatim but is also designed to identify cases of reuse when the original has been rewritten. The approach identifies reuse by comparing word n-grams in documents and modi...

Materials and Methods. In this article, we present a computer-assisted WML segmentation method, based on local f tures extracted from multiparametric magnetic resonance imaging (MRI) sequences (ie, T1-weighted, T2-weighted, pro density-weighted, and fluid attenuation inversion recovery MRI scans). A support vector machine classifier is first tr on expert-defined WMLs, and is then used to classi...

This paper presents a simple and effective method for image contrast enhancement called spatially weighted histogram equalization. Spatially weighted histogram not only considers the times of each grey value appears in a certain image, but also takes the local characteristics of each pixel into account. In the homogeneous region of an image, the spatial weights of pixels tend to zero, whereas a...

The spectrum of the Laplacian, signless Laplacian and adjacency matrices of the family of the weighted graphs R{H}, obtained from a connected weighted graph R on r vertices and r copies of a modified Bethe tree H by identifying the root of the i-th copy of H with the i-th vertex of R, is determined.

-------------------------------------------------------------------ABSTRACT--------------------------------------------------------------Mining Frequent Patterns is one of the primary step in Association Rule Mining (ARM). ARM always aims to produce relationships between different attributes of a database. Sometimes we may require including the weights (or significance) of different attributes ...