Fumiyasu Makinoshima

Abstract On 1 January 2024, the Noto Peninsula earthquake generated a devastating tsunami that struck coastal areas within several minutes, yet resulted in few tsunami casualties. Despite its importance, the cause of this unexpectedly low human loss remained unclear, as conventional surveys were hindered by the limited access and the presence of many visitors during the holiday.

[Submitted on 31 Jul 2025 ( v1 ), last revised 29 Aug 2025 (this version, v2)] Title:Designing Dynamic Pricing for Bike-sharing Systems via Differentiable Agent-based Simulation View a PDF of the paper titled Designing Dynamic Pricing for Bike-sharing Systems via Differentiable Agent-based Simulation, by Tatsuya Mitomi and Fumiyasu Makinoshima and Fumiya Makihara and Eigo Segawa View PDF HTML (experimental) Abstract:Bike-sharing systems are emerging in various cities as a new ecofriendly...

Abstract Rapid and accurate hazard forecasting is important for prompt evacuations and reducing casualties during natural disasters. In the decade since the 2011 Tohoku tsunami, various tsunami forecasting methods using real-time data have been proposed. However, rapid and accurate tsunami inundation forecasting in coastal areas remains challenging. Here, we propose a tsunami forecasting approach using convolutional neural networks (CNNs) for early warning.