Kernel density estimators are the basic tools for density estimation in non-parametric statistics. The k-nearest neighbor kernel estimators represent a special form of kernel density estimators, in which the bandwidth is varied...

to predict financial distress of Iranian firms, with four techniques: support vector machines, artificial neural networks (ANN), k-nearest neighbor and naïve bayesian classifier by using accounting information of the firms for two years prior to financial...

this information. A new method that uses neighbor and link concepts has more suitable performance than previous methods in this field. Two documents are neighbors if their similarity is more than a defined threshold. If they are neighbors, neighbor matrix element...

Topology control, wherein nodes adjust their transmission ranges to conserve energy is an important feature in wireless ad hoc networks. In this paper we propose a power control protocol based on neighbor detection for conserving energy...