In condition monitoring (CM) signal analysis the inherent problem of key characteristics being masked by noise can be addressed by analysis of the signal envelope. Envelope analysis of vibration signals is effective in extracting useful information for diagnosing different faults. However, the number of envelope features is generally too large to be effectively incorporated in system models. In...

A central problem in analysis of gene expression data is clustering of genes with similar expression profiles. In this paper, I describe an hierarchical clustering procedure that is based on simple probabilistic model. This procedure clusters genes with respect to a target classification of conditions, so that genes that are expressed similarly in each group of conditions are clustered together.

Vector-space and distributional methods for text document clustering are discussed. Discriminative clustering, a recently proposed method, uses external data to find taskrelevant characteristics of the documents, yet the clustering is defined even with no external data. We introduce a distributional version of discriminative clustering that represents text documents as probability distributions...

In this work, a hierarchical ensemble of projected clustering algorithm for high-dimensional data is proposed. The basic concept of the algorithm is based on the active learning method (ALM) which is a fuzzy learning scheme, inspired by some behavioral features of human brain functionality. High-dimensional unsupervised active learning method (HUALM) is a clustering algorithm which blurs the da...

In this paper, we present experimental results on document clustering and classification achieved on the Arabic NEWSWIRE corpus using statistical methods. Arabic is a highly inflecting language. The methods presented here show to be very robust and reliable without morphological analysis.

In condition monitoring (CM) signal analysis the inherent problem of key characteristics being masked by noise can be addressed by analysis of the signal envelope. Envelope analysis of vibration signals is effective in extracting useful information for diagnosing different faults. However, the number of envelope features is generally too large to be effectively incorporated in system models. In...

In this study, Neutrophic normed spaces, which is one of the popular mathematics topics recent times, discussed. The Neutrosophic approach, argues that it insufficient to evaluate problems in daily life as just right and wrong, based on principle degree indecision should be taken into account. Now, rough statistical convergence triple sequences defined spaces. Moreover, important topological pr...

Subspace clustering developed from the group of cluster objects in all subspaces of a dataset. When clustering high dimensional objects, the accuracy and efficiency of traditional clustering algorithms are very poor, because data objects may belong to diverse clusters in different subspaces comprised of different combinations of dimensions. To overcome the above issue, we are going to implement...

We consider the Ordered Cluster Traveling Salesman Problem (OCTSP). In this problem, a vehicle starting and ending at a given depot must visit a set of n points. The points are partitioned intoK,K n, prespeci ed clusters. The vehicle must rst visit the points in cluster 1, then the points in cluster 2, : : :, and nally the points in cluster K so that the distance traveled is minimized. We prese...