Results 51 to 60 of about 5,037 (157)

A prediction rigidity formalism for low-cost uncertainties in trained neural networks

Machine Learning: Science and Technology
Quantifying the uncertainty of regression models is essential to ensure their reliability, particularly since their application often extends beyond their training domain.
Filippo Bigi, Sanggyu Chong, Michele Ceriotti, Federico Grasselli   +3 more
doaj   +1 more source

International Meteorological and Hydrological Training and Its Evaluation at WMO RTC Nanjing

Procedia Environmental Sciences, 2012
AbstractThis paper deals with the international meteorological and hydrological training issue and its evaluation approach based on the teaching practice and experience during last twenty years at World Meteorological Organization Regional Training Centre (WMO RTC) in Nanjing.
Zhi, Xiefei, Yang, Hao, Zhang, Ling, Chen, Wen, Wang, Yong   +4 more
openaire   +1 more source

Integration of sentinel surveillance and climate factors to accelerate malaria elimination in a changing climate of Senegal

Science in One Health
Background: Senegal is located in a malaria-endemic zone. Malaria is a highly climate-sensitive vector-borne disease, yet its sentinel surveillance shows a weak integration of malaria morbidity data with climatic factors.
Ibrahima Mamby Keita, Mariama Diouf, Medoune Ndiop, Boly Diop, Khaly Gueye, Marianne Kouawo, Ousmane Ndiaye, Doudou Sene, Elhadji Mamadou Ndiaye, Marie Khemesse Ngom Ndiaye   +9 more
doaj   +1 more source

OPERANDUM Training Materials: Nature-based Solutions for Hydro-Meteorological Hazards

, 2022
The OPERANDUM training materials aim to emphasize the knowledge generated through the EU-funded OPERANDUM project and promote the uptake of Nature-based Solutions for hydro-meteorological hazards in Europe and beyond. Embedded in a series of training units, the materials address common knowledge gaps and highlight lessons learned from the NBS co ...
openaire   +1 more source

Characterization of secondary organic aerosol formation and evolution from coal combustion utilizing an oxidation flow reactor

Environmental Research Communications
Coal combustion (CC) represents an important contributor of the atmospheric primary particulate matter and drives a large fraction of secondary organic aerosol (SOA) formation in cold season.
Zhijie Li, Weiqi Xu, Wei Zhou, Wei Yuan, Bo You, Chun Chen, Fang Zhang, Wenjie Fan, Yele Sun   +8 more
doaj   +1 more source

Adaptability evaluation of the FIRST model in Hobq Desert, northern China

Frontiers in Earth Science
Obtaining high temporal and spatial resolution spectral data is the key to revealing the influencing factors, effects, and mechanisms of land-atmosphere interactions in deserts.
Xinqian Zheng, Fan Yang, Jingshu Wang, Lishuai Xu, Silalan Abudukade, Mingjie Ma, Yingwei Sun   +6 more
doaj   +1 more source

Risk evaluation of low temperature disaster in greenhouses based on GIS spatial analysis under climate change: a case study in Hebei province, China

Open Geosciences
To improve the scientific planning of crop cultivation regions, enhance crop quality, mitigate meteorological disaster risks, and optimize the utilization of climatic resources, this study analyzed temperature data from 141 national meteorological ...
Le Zhangyan, Shi Minghua, Liao Rongwei, Liu Huaiyu, Geng Xueying, Zhou Peng, Wei Qucheng, Zhang Yanyan, Hou Qiqi, Yu Hong, Ma Fenglian, Zhang Jibo, Sun Lihua   +12 more
doaj   +1 more source

Neural Phase Picker Trained on the Japan Meteorological Agency Unified Earthquake Catalog

Earth, Planets and Space
Abstract In Japan, one of the most seismically active nations, seismic data from various institutions are shared in real-time and made accessible via the web, which facilitates research by numerous scholars. The Japan Meteorological Agency (JMA), in collaboration with the Ministry of Education, Culture, Sports, Science, and Technology (MEXT ...
Makoto Naoi, Koji Tamaribuchi, Kengo Shimojo, Shinya Katoh, Shukei Ohyanagi   +4 more
openaire   +2 more sources

Loss Adaptive Curriculum Learning for Ground-Based Cloud Detection

Remote Sensing
While deep learning has advanced object detection through hierarchical feature learning and end-to-end optimization, conventional random sampling paradigms exhibit critical limitations in addressing hyperspectral ambiguity and low-distinguishability ...
Tianhong Qi, Yanyan Hu, Juan Wang
doaj   +1 more source

Assessing future flood hazards in the major rivers of Bangladesh using CMIP6 projections and integrated hydrologic-hydraulic modeling

Applied Computing and Geosciences
Climate change is expected to significantly alter flood dynamics in Bangladesh, one of the world's most flood-prone countries. Yet quantitative assessments of future flood hazards in this region remain sparse.
Aishia Fyruz Aishi, Md Kamruzzaman Tusar, Md Ariful Islam   +2 more
doaj   +1 more source