Clustering problems arise in various domains of science and engineering. A large number of methods have been developed to date. The Kohonen self-organizing map (SOM) is a popular tool that maps a high-dimensional space onto a small number of dimensions by placing similar elements close together, forming clusters. Cluster analysis is often left to the user. In this paper we present the method Tr...

introduction:surgeosight is a dedicated intra-operative hand-held gamma camera designed and manufactured by our team to be used for lymphoscintigraphy. although conventional gamma cameras are widely used, they lack the capability of the sentinel lymph node (sln) imaging in the operation room. like conventional gamma cameras it is necessary to calibrate surgeosight for linearity distortion, ener...

Content-based video navigation is an efficient method for browsing video information. A common approach is to cluster shots into groups and visualize them afterwards. In this paper, we present a prototype that follows in general this approach. Unlike the existing systems, the clustering is based on a growing self-organizing map algorithm. We focus on studying the applicability of SOMs for video...

Semantic multimedia organization is an open challenge. In this chapter, we present an innovative way of automatically organizing multimedia information to facilitate content-based browsing. It is based on self-organizing maps. The visualization capabilities of the self-organizing map provide an intuitive way of representing the distribution of data as well as the object similarities. The main i...

Abstract Identifying community structure is an important issue in network science and has attracted attention of researchers in many fields. It is relevant for social tasks, biological inquires, and technological problems. In this paper, we proposed a new approach based on self-organizing map to community detection. By using a proper weight-updating scheme, a network can be organized into dense...

The Growing Self Organizing Map (GSOM) is a dynamic variant of the Self Organizing Map (SOM). It has been mainly used on low dimensional data sets. In this paper the GSOM is applied on high dimensional data sets and its performance is evaluated. Several modifications to the original GSOM algorithm are presented that enable the GSOM to be applied on high dimensional data .The modified version of...

The usual first step in analyzing the large and high-dimensional data sets measured by microarrays is visual exploration. In this work self-organizing maps have been used to visualize similarity relationships of data samples. In all unsupervised data analysis methods the measure of similarity determines the result; we propose to use the learning metrics principle to derive a metric from interre...

The classification of fuzzy data is considered as the most challenging areas of data analysis and the complexity of the procedures has been obstacle to the development of new methods for fuzzy data analysis. However, there are significant advances in modeling systems in which fuzzy data are available in the field of mathematical programming. In order to exploit the results of the researches on ...

Background: The present study evaluated the lifestyle behavior patterns and its associations with demographic factors in the Iranian population. Methods: A total of 8244 people aged 25-70 years who participated in a national survey in 2011 were included in the study. Factors related to lifestyle (such as diet, physical activity, and tobacco use) have been collected using a questionnaire. A sel...