Anxious and avoidant attachment were assessed in the Children in the Community (CIC) Study during adolescence and adulthood using self-report scales developed for this prospective study. The convergent and discriminant validity of the new CIC attachment scales were evaluated and their stability was assessed across a 17-year interval. Attachment scales predicted DSM-IV personality disorders in t...

A multiresolution color image segmentation method is presented that incorporates the main principles of region-based and cluster analysis approaches. A multiscale dissimilarity measure in the feature space is proposed that makes use of non-parametric cluster validity analysis and fuzzy C-Means clustering. Detected clusters are utilized to assign membership functions to the image regions. In add...

Rough K-means algorithm has shown that it can provides a reasonable set of lower and upper bounds for a given dataset. With the conceptions of the lower and upper approximate sets, rough k-means clustering and its emerging derivatives become valid algorithms in vague information clustering. However, the most available algorithms ignore the difference of the distances between data objects and cl...

The increasingly larger scale of available data and the more restrictive concerns on their privacy are some of the challenging aspects of data mining today. In this paper, Entropy-based Consensus on Cluster Centers (EC3) is introduced for clustering in distributed systems with a consideration for confidentiality of data; i.e. it is the negotiations among local cluster centers that are used in t...

The result of one clustering algorithm varies from that of another for the same input dataset as the input parameters of an algorithms can substantially affect the behavior and execution of the algorithms. Cluster validity measures can be used to find the partitioning that best fits the underlying data. In most realistic applications, this analysis can be visualized using simple Computer-Aided-...