Invited Talk 1
Presenter:
Prof. Shinji Shimojo
Aomori University
President of Global Environment Center
Title:
Cycling Towards Smarter Cities: Lessons from Osaka’s Data Commons and Aomori’s Urban Innovation
Abstract:
This keynote will explore the evolving landscape of smart cities through a unique lens, drawing upon the speaker’s direct experiences and ongoing research. It begins by delving into the pioneering efforts of urban sensing via bicycles, demonstrating how data can provide invaluable insights into the pulse of a city and empower grassroots community revitalization. The discussion will then shift to the foundational importance of common data platforms, specifically highlighting the speaker’s involvement in building such infrastructure in Osaka. We’ll examine the challenges and triumphs of creating a shared data ecosystem that can facilitate collaboration and innovation across various urban services. Then we’ll journey north to Aomori, where we’ll explore local smart city initiatives and reflect on their distinctive approach to urban development. Through these diverse case studies, this presentation aims to foster a critical re-evaluation of what truly constitutes a “smart” city, advocating for approaches that are not only technologically advanced but also deeply integrated with local context and citizen participation.
Biography:
Shinji Shimojo received the M.E. and Ph.D. degrees from Osaka University in 1983 and 1986, respectively. He is a professor at Aomori University. His current research work is focusing on a smart city, ubiquitous network systems, and IoT systems. He is a founding member of PRAGMA and CENTRA. From Aug. 2023, he served a APAN chair. He was awarded the Osaka Science Prize in 2005 and by the Minister of Internal Affairs in 2017. He is a member of IEEE, IEICE fellow, and IPSJ fellow.
Invited Talk 2
Presenter:
Prof. Akio Doi
CEO of i-Plants Systems Ltd.
Specially Appointed Professor at Iwate Prefectural University
Title:
Preliminary Study on 3D Modeling of the Reactor Interior Using Underwater ROV Video Footage from the Fukushima Daiichi Nuclear Power Plant
Abstract:
A preliminary investigation was conducted into methods for generating 3D models of the reactor interior at the Fukushima Daiichi Nuclear Power Plant using video footage acquired by underwater remotely operated vehicles (ROVs). The reconstruction methods evaluated included COLMAP, Reality Capture, DUSt3R, and MASt3R. While COLMAP and Reality Capture are classified as part of the computer vision (CV) generation, DUSt3R and MASt3R represent the artificial intelligence (AI) generation, and the underlying generation algorithms differ significantly. The overall workflow consists of three stages: (1) Preprocessing of video frames, (2) 3D point cloud generation, and (3) Real-time meshing and visualization. During the preprocessing stage, a custom image processing program was developed to remove floating objects and overlaid captions.
Biography:
Akio Doi received his master’s degree from the Graduate School of Engineering at Kobe University in 1982, the same year he joined IBM Japan, Ltd. In 1999, he was appointed as a professor at the Faculty of Software and Information Science, Iwate Prefectural University, where he served until his retirement in March 2023. He is currently the CEO of i-Plants Systems Ltd. and serves as a Specially Appointed Professor at Iwate Prefectural University. His research interests include computer graphics, image processing, and artificial intelligence. His company’s main products include Volume Extractor 3.0 and JointVision 2.0. He is also a co-author of the book Basics and Applications of 3D Graphics.
URL: http://advancedvislab.com/
URL: http://www.i-plants.jp/hp/
e-mail: doia@iwate-pu.ac.jp
Invited Talk 3
Presenter:
Prof. Hao Wang
Complex Global Simulation Unit
National Institute for Fusion Science
Title:
Preliminary simulation results of energetic particle driven instabilities in VAST stellarator
Abstract:
A new conceptual stellarator device named Variable Symmetry Torus (VAST) is being designed to generate various magnetic configurations with distinct symmetries, including quasi-axisymmetric (QA) and quasi-isodynamic (QI) configurations. Preliminary simulation results of energetic particle driven instabilities in VAST have been obtained with a first-principles hybrid code, MEGA. Alfven eigenmodes are destabilized under the condition of tangentially injected neutral beam. The mode numbers are m/n = 10/4 and 11/4 in QA configuration, and they are m/n = 5/2 and 4/2 in QI configuration. The frequencies are 91 kHz and 107 kHz in QA and QI, respectively. The destabilized modes are preliminarily identified as beta-induced Alfven eigenmodes (BAEs). The destabilization of BAE mode in QI configuration is clearly more difficult than that in QA configuration, and this difference may be caused by the special rotational transform profile or the strong toroidal variation of magnetic field strength in QI. Strong energetic particle redistributions are found in both QA and QI configurations during BAE activities.
Biography:
Dr. Hao WANG received a bachelor’s degree from Xi’an Jiaotong University and a master’s degree from the Southwestern Institute of Physics in China. Then, he moved to Japan and received his Ph.D. from SOKENDAI (The Graduate University for Advanced Studies) in 2012. Currently, he is an assistant professor at the National Institute for Fusion Science. His research interests include plasma physics simulation and machine learning. Dr. WANG has published over 50 peer-reviewed articles in journals such as Physical Review Letters, Scientific Reports, and Nuclear Fusion. His h-index is 15 and i10-index is 17. He has received the Award for Notable Contribution to Technology from JSPF (The Japan Society of Plasma Science and Nuclear Fusion Research) and the Young Scientist Award from JPS (The Physical Society of Japan).