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Titlebook: Computational Science – ICCS 2024; 24th International C Leonardo Franco,Clélia de Mulatier,Peter M. A. Slo Conference proceedings 2024 The

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XLTU: A Cross-Lingual Model in Temporal Expression Extraction for Uyghur downstream tasks such as logical reasoning and information retrieval. However, current TEE research mainly focuses on resource-rich languages like English, leaving a gap for minor languages (e.g. Uyghur) in research. To address these issues, we create an English-Uyghur cross-lingual dataset specifi
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Modeling Tsunami Waves at the Coastline of Valparaiso Area of Chile with Physics Informed Neural Net.8, where 597 people were killed. The most dangerous earthquakes occur at the bottom of the ocean. The tsunamis they cause are very dangerous for residents of the surrounding coasts. In 2010, as many as 525 people died in a destructive tsunami caused by an underwater earthquake. Our research paper a
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Simulation Model for Application of the SDN Concept in IMS/NGN Network Transport Stratuma Subsystem/Next Generation Network (IMS/NGN) and Software-Defined Networking (SDN). Application of the SDN architecture elements in IMS/NGN networks will enable unified control and management of transport resources for various transport technologies and equipment manufacturers. However, such a coop
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Cascade Training as a Tree Search with Dijkstra’s Algorithm on the . technique. The reason behind the algorithm change is reduction of training time. This change does not affect in anyway the quality of the final classifier. We conduct experiments on cascades trained to become face or letter detectors with Haar-like features or Zernike moments being the inp
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Optimizing Prescribed Burn Risk Management: A Computational and Economic Modeling Approach Using QUIiciency and cost-effectiveness of a prescribed burn for planned reduction of vegetation density. The QUIC FIRE simulation tool is employed to conduct simulations across fireline widths ranging from 8 to 24 m in 2-m increments within a strategically chosen burn unit that covers the usecase of a wildl
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https://doi.org/10.1007/978-1-4612-2628-4eta-model is trained using patterns most similar to the query pattern. Through extensive experimental studies across 35 forecasting scenarios and employing 16 base forecasting models, our findings underscored the superiority of quantile regression forest over its competitors.
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