The WSO M (Wavelet SelfOrganizing 1\Jap) model, a rwural network for the erea.tion of wavelet bases adapted to the distribution of input data, is introduced. The model provides an efficient on-lim) way to construct high-dimensional wavelet bases. Simulations of a lD function approximation problem illustrate how WSOM adapts to non-uniformly distributed input data, outperforming the discrete wa.v...

Large-scale simulations of time-dependent problems generate a massive amount data and with the explosive increase in computational resources size generated by these has increased significantly. This imposed severe limitations on that can be stored elevated issue input/output (I/O) into one major bottlenecks high-performance computing. In this work, we present an situ compression technique to re...

Accepted on 25 th August 2014 _____________________________________________________________________________ ABSTRACT Synthesis of symmetrical Schiff bases (1-4) employed by using condensation methods. Purity was monitored by TLC and column chromatographic techniques. In this present study cyclic voltammetric behavior of symmetrical Schiff bases (1-4) were studied. The cyclic voltammetric studie...

In this paper we present a methodology for goal-directed data mining of association rules and incorporation of these rules into a probabilistic knowledge base. The purpose of the data mining and rule extraction process is to repair knowledge base incompleteness uncovered during validation. We discuss how this incompleteness is uncovered and show the fundamental forms this incompleteness can tak...