Perceptual grouping is crucial to distinguish objects from their background. Recent studies have shown that observers can detect an object that does not have any unique qualities other than unique temporal properties. A crucial question is whether focused attention is needed for this type of grouping. In two visual search experiments, we show that searching for an object defined by temporal gro...

The authors conducted a systematic review of the literature for scientific articles in selected databases to determine the effects of aging on Type II muscle fibers in human skeletal muscles. They found that aging of Type II muscle fibers is primarily associated with a loss of fibers and a decrease in fiber size. Morphological changes with increasing age particularly included Type II fiber grou...

We introduce the problem of cluster-grouping and show that it integrates several important data mining tasks, i.e. subgroup discovery, mining correlated patterns and aspects from clustering. The problem of cluster-grouping can be regarded as a new type of inductive optimization query that asks for the k best patterns according to a convex criterion. The algorithm CG for solving cluster-grouping...

In this paper, we present a technique for grouping line segments sinto convex sets, where the line segments are obtained by linking edges obtained from the Canny edge detector. The novelty of the approach is twofold: rst we de ne an e cient approach for testing the global convexity criterion, and second, we develop an optimal search based on dynamic programming or grouping the line segments int...

In this paper, we present a technique for grouping line segments into convex sets, where the line segments are obtained by linking edges obtained from the Canny edge detector. The novelty of the approach is twofold: first we define an efficient approach for testing the global convexity criterion, and second, we develop an optimal search based on dynamic programming for grouping the line segment...

Due to increase of the mining of compressed data from various types of applications. Clustering is the process for resolving that type of applications. Traditionally we are using different clustering applications for grouping elements with equal priority. And we represent single clustering process with multi dimensional data grouping using clustering but the only problem is performance of group...