Institute of Disaster Prevention

Hydrochemistry and modeling nitrate concentration in farmland groundwater under different hydrological seasons by integrating hybrid quantum-classical ML, virtual sample generation and AlphaEarth Foundation

Abstract. Precise seasonal prediction of groundwater nitrate concentrations in intensive agricultural areas faces challenges such as data sparsity, strong spatiotemporal heterogeneity, and complex hydro-biogeochemical processes. To address these issues, this study proposes an int...

Geometric Invariant Moment-Based Feature Extraction for Cognitive Load Monitoring

EEG-based cognitive workload assessment has attracted considerable attention in fields such as brain–computer interfaces and human–computer interaction due to its high temporal resolution and non-invasive nature. However, existing studies mainly focus on time-domain and frequency...

Assessing Land Cover Change and Forest Sustainability in a World Heritage Context: Evidence from the Okapi Wildlife Reserve

Long-term monitoring of land cover dynamics is essential for evaluating conservation outcomes in World Heritage sites, yet remains challenging in conflict-affected regions with limited field observations. This study aims to reconstruct annual land cover dynamics and assess forest...

Effects of triply periodic minimal surface porous media structures on combustion and heat transfer characteristics of low-concentration methane

Porous medium burners can improve the combustion efficiency of low concentration methane, promote the utilization of low grade energy sources, and reduce greenhouse gas emissions. As a new type of porous medium, it is of great significance to investigate the effects of different...

Dynamic Evaluation of Fire Service Accessibility for Fireworks Manufacturers

Although fire service accessibility has been extensively studied for urban public facilities such as hospitals and parks, it remains largely unexplored for high-risk industrial facilities such as fireworks manufacturers. In this study, fire risk and transportation network conditi...

Time–frequency collaborative denoising for audio-magnetotelluric data using a wavelet-based residual network

Abstract The Audio-Magnetotelluric (AMT) method is a key geophysical technique for mineral resource exploration, but anthropogenic electromagnetic interference severely downgrades the data quality. In recent years, neural networks have shown results superior to traditional method...