会议报告

Koji Koyamada

Koji Koyamada Kyoto University
Koji Koyamada received a B.S., M.S. and Ph.D degrees in electronic engineering from Kyoto University, Kyoto, Japan in 1983, 1985, and 1994, respectively. He is a professor at Kyoto University. From 1985 to 1998 he worked for IBM Japan. From 1998 to 2001 he was an associate professor at Iwate Prefectual University. From 2001 to 2003 he was an associate professor at Kyoto University. His research interest includes modeling, simulation and visualization. He is a member of IEEE Computer Society, directors of Visualization Society Japan, and the Institute of Systems, Control and Information Engineers and a president of Japan Society of Simulation Technology. He received the IEMT/IMC outstanding paper award in 1998, the VSJ contribution award in 2009 and the VSJ outstanding paper award in 2010.

Trends in Japanese Visualization Community
In this talk, we will introduce some activities of visualization society in Japan (VSJ). The VSJ started as a flow visualization society and is now integrated with information visualization community. From 1996, the VSJ has organized the largest visualization conference in Japan, which is composed of invited presentations and commercial exhibitions. In the VSJ, we initiated a special interested group on visual data mining from 2001. In this SIG, we have discussed on several topics on visualization. Our topic that has attracted much interest in the SIG is particle graphics (PG). The PG becomes one of effective solutions when the number of semi-transparent graphics objects is huge and the visibility sorting is difficult. Thus, the PG has been selected as a core technology for visualizing a huge simulation result in the Japanese fastest computer system, the K computer. We show its technological overview and our future plan on its enhancement.
Prediction of the fishing ground using visualization techniques
In this talk, we will describe a role of visualization techniques for the fishing ground prediction. Recently, the prediction technologies are highly expected in the fishery industry. Due to the global warming, the fishery is getting difficult. On the other hand, the accuracy of the atmosphere and ocean simulation has been improved since the modeling technologies and the computing power are advanced noticeably. In the prediction, we develop a habitat suitability index (HSI) model using the simulation results and catch per unit effort (CPUE) data. In the development, we first select variables which have high correlations with CPUE to draw a suitable index (SI) in the variable space and then construct a HSI model using these SI equations. To validate the model, we visualize the HSI distribution in the coordinate space. Currently, we are developing a user interface in which fishermen can construct their own HSI map.