The paper tries to study the effect of participation pattern on sport activities among the students of I.A.U of Kermanshah. The research method is survey with questionnaire and 368 students were chosen through cluster sampling. The data were analyzed by SPPS(version of 11.5). The results show the median of participation pattern is 2.31 and 1.14 out of students and it was in lower stage, but the...

In this paper we present our visual analysis results of visitor movement data in an amusement park during a weekend. We assume most people move among several amusement park spots in a specific pattern. And for few people whose movement pattern don’t belong to any group we assume, we pay special concern about their route for they may related to a crime happened in amusement park during the weeke...

Broline, Crowe and Isaacs have computed the determinant of a matrix associated to a Conway-Coxeter frieze pattern. We generalise their result to the corresponding frieze pattern of cluster variables arising from the Fomin-Zelevinsky cluster algebra of type A. We give a representation-theoretic interpretation of this result in terms of certain configurations of indecomposable objects in the root...

The fundamental goal of this research has been to improve computational efficiency of the Visually Empirical Region of Influence (VERI) 1 based clustering and pattern recognition (PR) algorithms we developed in previous work. The original clustering algorithm, when applied to data sets with N points, ran in time proportional to N 3 (denoted with the notation O (N 3)), which limited the size of ...

The global pattern mining step in existing pattern-based hierarchical clustering algorithms may result in an unpredictable number of patterns. In this paper, we propose IDHC, a pattern-based hierarchical clustering algorithm that builds a cluster hierarchy without mining for globally significant patterns. IDHC allows each instance to "vote" for its representative size-2 patterns in a way that e...

A new pattern clustering method based on the Karhunen-Loeve expansion and moment-preserving thresholding is proposed. For a given set of unlabeled, nonparametric patterns with the number of clusters unknown a priori, if the patterns in each cluster are densely populated and the region between any two clusters is sparsely populated, then the proposed method can be employed to classify the patter...

Cluster analysis finds its place in many applications especially in data analysis, image processing, pattern recognition, market research by grouping customers based on purchasing pattern, classifying documents on web for information discovery, outlier detection applications and act as a tool to gain insight into the distribution of data to observe characteristics of each cluster. This ensures ...

Clustering algorithms gives general description of the clusters listing number of clusters and member entities in those clusters. It lacks in generating cluster description in the form of pattern. Deriving pattern from clusters along with grouping of data into clusters is important from data mining perspective. In the proposed approach reduct from rough set theory is employed to generate patter...

Secure data transmission and data aggregation are critical in designing cluster-based sensor networks. This paper presents an Energy-efficient and Secure Pattern-based Data Aggregation protocol (ESPDA) for wireless sensor networks. ESPDA is energy and bandwidth efficient because cluster-heads prevent the transmission of redundant data from sensor nodes. ESPDA is also secure because it does not ...