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This paper explores the application of convolutional neural networks (CNNs) in predictive modelling for seismic events and flood risks, with a particular focus on forecasting extreme quantile events that exceed historica...

Third-generation biomass constitutes a renewable energy source that could substitute fossil fuels. This study evaluated the biomethane potential (BMP) of Ulva sp., Codium sp. and Undaria pinnatifida through anaerobic dig...

Abstract Echo State Networks are recurrent neural networks that leverage a random reservoir’s dynamics, training only a simple readout layer. This approach is computationally efficient but limits network performance. B...

Drought is a slow-onset natural disaster that has far-reaching effects on agriculture, water security, and socio-economic systems, especially in climate-vulnerable countries such as Malaysia. It is imperative to predict ...

Dear Readers,It gives me great pleasure to announce the fourth regular issue of 2026. In this issue, 6 papers by 25 authors from 6 countries - Colombia, Greece, Mexico, Republic of Serbia, South Africa, Türkiye ...

Many classification systems rely on clustering techniques in which a collection of training examples is provided as an input, and a number of clusters c1,...cm modelling some concept C results as an output, such that ev...

Subjects / keywords: positron emission tomography, magnetic resonance imaging, single-photon emission tomography, non-invasive brain imaging, neural systems modelling, neuroanatomy; Medicine: Medicine (General): Medical technology; Medicine:...

The search for new energy sources has intensified today worldwide. In Argentina, bioenergy continues to be the energy with minor participation in the energy matrix. Therefore, research should focus on searching for new s...

Abstract Recognizing tactical formations is a critical task in professional football performance analytics. However, existing methods often fail to capture the dynamic and continuously evolving nature of modern tactical ...

A solution of problems in multiagent systems involves representing beliefs of agents immersed in dynamic environments. Observation-based Defeasible Logic Programming (ODeLP) is an argument-based logic programming languag...