JSST2023 Symposiums

Symposium1: Advanced Concept and Methodology in Bioscience

OrganizerTakahiro Kenmotsu (Doshisha Univ.)
Co-organizerSusumu Fujiwara (Kyoto Inst. of Tech.), Hiroaki Nakamura (NIFS) and Yoshihide Shibata (National Inst. Tech. Gifu College)
ObjectiveWe focus on research of advanced concept and methodology in the field of bioscience including origin of life, numerical calculation including theoretical treatment, data analysis in medical field and so on. The aim of this symposium is to provide a forum for exchanging ideas and developing concept including numerical methodology. We expect that participants launch new concepts and collaborations in bioscience by fruitful discussion in this session.

Symposium2: Simulation, machine learning and/or XR for science and technology

OrganizerHiroaki Ohtani (NIFS)
Co-organizerSeiki Saito (Yamagata Univ.), Kazuo Hoshino (Keio Univ.), Shunsuke Usami (NIFS), Satoshi Togo (Univ. of Tsukuba), Yuichi Tamura (Konan Univ.) and Nobuaki Ohno (Univ. of Hyogo)
ObjectiveNumerical simulation based on the fundamental laws of nature provides an understanding of complex phenomenon in the the physical world, and the numerical simulation achieves success in an attempt to project the phenomenon in the physical world onto the cyber space. In addition to that, accuracy improvement of measurement tools gives us abundant experiment and observation data, and it becomes possible to find a relationship among the data by machine learning. The machine learning gives us information on the correlation among the data even if the combination of the fundamental laws cannot explain the phenomenon.
Analysis by XR (VR, AR and MR) is absolutely essential not only in science and technology but also in disaster prevention, social science, informatics science and so on. Combination of XR analysis and machine learning is also recently developed. Advanced visualization technology and method play an increasingly significant role.
From this kind of circumstance, integration of numerical simulation, machine learning and XR is expected to open the new way to understand phenomenon.
The aim of this symposium is to introduce state-of-the art results concerned with simulation, machine learning and/or XR in science and technology, such as fusion science, plasma physics, material science, biological science, social science, informatics science and so on, and to provide a forum for exchanging ideas and discussing recent developments of them.

Symposium3: Multi-Dimensional Communication Networks

OrganizerKeisuke Nakano (Niigata Univ.)
Co-organizerKenichi Ito (Niigata Inst. Tech.)
ObjectiveCommunication networks keep evolving in various directions. These networks become complicated, and various types of networks such as MANET, DTN and social networks arise. The concept of the multi-dimensional communication networks stands for such evolving networks toward various dimensions.  The aim of this symposium is to discuss the latest issues related to the multi-dimensional networks.