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The data visualization, which reduces data dimension to make us easy to see data directly, is important in data mining. It is important that one category becomes one cluster (we define this as data cohesion) and the clusters are standoff to each other (we define this as cluster separation) in data visualization. In this paper, we propose a self-organizing method using data movement on a spherical surface for data visualization. The proposed method puts all data points on the spherical surface and each data point moves on the spherical surface under the force from all the other data points. The key features of the proposed method are using a spherical surface as output space and employing weighted inter-point distance which emphasizes similarity between these data points. The experimental results show that the proposed method visualizes data with high data cohesion and high cluster separation by dint of above features.

In this paper, first, FDTD, semi-implicit method for pressure linked equations (SIMPLE), Monte Carlo and radiative energy absorption distribution (READ) methods are combined to calculate electromagnetic field and all the heat transfer phenomena of heat transport, heat transfer by air convection and heat radiation (It is called FDTD-SIMPLE-MR method.). The temperature distribution of an one-layer EM-absorber using a lossy dielectric material under high power injection is calculated using FDTD-SIMPLE-MR method and a traditional method. And the both calculated temperature distributions of the absorber are compared. As a result, the more detailed temperature distribution of the absorber is obtained by FDTD-SIMPLE-MR method.

In this paper, first, FDTD, Semi-Implicit Method for Pressure Linked Equations (SIMPLE), Monte Carlo and Radiative Energy Absorption Distribution (READ) methods are combined to calculate electromagnetic field and all the heat transfer phenomena of heat transport, heat transfer by air convection and heat radiation (It is called FDTD-SIMPLE-MR method.). The temperature distribution of λ/4 type EM-absorber using resistive film under high power injection is calculated using FDTD-SIMPLE-MR method. Next, the high power injection experiment is conducted using an absorber and high power RF instruments to get the temperature distribution experimentally. Finally, the calculated and measured temperature distributions of the absorber are compared. As a result, the calculated temperature distribution by FDTD-SIMPLE-MR method agrees well with the measured one and the validity of FDTD-SIMPLE-MR method is confirmed.

Analyzing users' Web log data and extracting their interests of Web-watching behaviors are important and challenging research topics of Web usage mining. Users visit their favorite sites and sometimes search new sites by performing keyword search on search engines. Users' Web-watching behaviors can be regarded as a graph since visited Web sites and entered search keywords are connected with each other in a time sequence. We call this graph as a site-keyword graph. This paper describes a method for clarifying users' interests based on an analysis of the site-keyword graph. The method is for extracting subgraphs representing users' routine visit from a site-keyword graph which is generated from augmented Web audience measurement data (Web log data). Experimental result shows that our new method succeeds in finding subgraphs which contain most of users' interested sites.