Results 31 to 40 of about 343 (133)

Evaluation of Forecast‐Based Global GNSS Precipitable Water Vapor Retrieval Using the AI‐Based Global Weather Forecast Model

Earth and Space Science, Volume 13, Issue 8, August 2026.
Abstract Real‐time water vapor monitoring is critical for meteorological applications such as weather forecasting and nowcasting. However, accurate real‐time retrieval of precipitable water vapor (PWV) from Global Navigation Satellite Systems (GNSS) remains challenging, especially for GNSS stations lacking meteorological sensors.
Wenjie Yin, Chen Zhou, Mengyi Zhong, Xiang Wang, Rong Tian, Wei Zhang, Yin Xiao, Hua Chen, Jian Kong, Qile Zhao, Yibin Yao   +10 more
wiley   +1 more source

Lexical Traces of AI: Linguistic Impact of Generative Tools in Academic Abstracts

Learned Publishing, Volume 39, Issue 3, July 2026.
ABSTRACT The widespread availability of generative AI tools is reshaping scholarly discourse at a linguistic level. This study investigates the diffusion of AI‐associated vocabulary in abstracts indexed in Scopus, focusing on post‐2022 patterns that emerged after the public release of tools such as ChatGPT.
Rubén Comas Forgas, Cinta Gallent Torres, Carmen Touza Garma, Alex Glynn   +3 more
wiley   +1 more source

MSWD: A Hybrid Machine‐Learning Framework for Slant Wet Delay Modeling

Journal of Geophysical Research: Atmospheres, Volume 131, Issue 12, 28 June 2026.
Abstract Space geodetic techniques such as Global Navigation Satellite Systems (GNSS) and Very Long Baseline Interferometry (VLBI) are limited by direction‐dependent tropospheric delays, with slant wet delay (SWD) being the most variable component and a major error source.
Zhenyi Zhang, Benedikt Soja
wiley   +1 more source

Random Forest-Based Model for Estimating Weighted Mean Temperature in Mainland China

Atmosphere, 2022
The weighted mean temperature (Tm) is a vital parameter for converting zenith wet delay (ZWD) into precipitation water vapor (PWV) and plays an essential part in the Global Navigation Satellite System (GNSS) inversion of PWV.
Haojie Li, Junyu Li, Lilong Liu, Liangke Huang, Qingzhi Zhao, Lv Zhou   +5 more
doaj   +1 more source

Large Language Models for Explainable Medical Text Summarization: A Systematic Literature Review

WIREs Data Mining and Knowledge Discovery, Volume 16, Issue 2, June 2026.
The graphical abstract highlights the three key aspects addressed in this review: the technical background of medical text summarization methods relevant to clinical decision support; the LLM background in providing context for its diagnosis and clinical significance; and clinical decision support with summarization and explainability in patient care ...
Aleka Melese Ayalew, Md Rabiul Hasan, Tapio Seppänen, Mourad Oussalah   +3 more
wiley   +1 more source

Assessment of the three representative empirical models for zenith tropospheric delay (ZTD) using the CMONOC data

Geodesy and Geodynamics
The precise correction of atmospheric zenith tropospheric delay (ZTD) is significant for the Global Navigation Satellite System (GNSS) performance regarding positioning accuracy and convergence time.
Debao Yuan, Jian Li, Yifan Yao, Fei Yang, Yingying Wang, Ran Chen, Tairan Xu   +6 more
doaj   +1 more source

A Window‐Augmented Machine Learning Approach for Direct GNSS Precipitable Water Vapor Retrieval

Journal of Geophysical Research: Machine Learning and Computation, Volume 3, Issue 2, April 2026.
Abstract Global Navigation Satellite Systems (GNSS) provide an effective means for remote sensing of precipitable water vapor (PWV). However, conventional GNSS‐based PWV retrieval approaches rely heavily on auxiliary meteorological parameters, which are frequently unavailable in real time, while most direct retrieval methods use station data aggregated
Zhouao Zheng, Haoyu Wang, Liangke Huang, Ziwei Li, Haojun Li, Hongxing Zhang, Junyu Li, Lilong Liu   +7 more
wiley   +1 more source

Exploring Influence Factors on LLM Suitability for No‐Code Development of End User Applications

Software: Practice and Experience, Volume 56, Issue 1, Page 96-118, January 2026.
ABSTRACT Context/Problem Statement No‐Code Development Platforms (NCDPs) empower non‐technical end users to build applications tailored to their specific demands without writing code. While NCDPs lower technical barriers, users still require some technical knowledge, for example, to structure process steps or define event‐action rules.
Minghe Wang, Alexandra Kapp, Trever Schirmer, Tobias Pfandzelter, David Bermbach   +4 more
wiley   +1 more source

Artificial Intelligence Applications in Smart Cities: Integrating Communication, Energy Management, Cybersecurity and Internet of Things

The Journal of Engineering, Volume 2026, Issue 1, January/December 2026.
ABSTRACT Smart cities represent transformative urban ecosystems, leveraging advanced technologies to address challenges posed by rapid urbanisation, energy efficiency demands, and sustainability goals. Despite extensive research, a comprehensive and integrated literature analysis combining AI‐based communication, energy management, cybersecurity, and ...
Maaz Tahir Malik, Hafiz Abdul Muqeet, Rizwan Akram, Hafiz Muhammad Obaid, Atiq ur Rehman, Amine Bermak   +5 more
wiley   +1 more source

Tibetan Few‐Shot Learning Model With Deep Contextualised Two‐Level Word Embeddings

CAAI Transactions on Intelligence Technology, Volume 10, Issue 5, Page 1394-1410, October 2025.
ABSTRACT Few‐shot learning is the task of identifying new text categories from a limited set of training examples. The two key challenges in few‐shot learning are insufficient understanding of new samples and imperfect modelling. The uniqueness of low‐resource languages lies in their limited linguistic resources, which directly leads to the difficulty ...
Ziyue Zhang, Yongbin Yu, Xiangxiang Wang, Xiao Feng, Yuze Li, Jiarun Shen, Dorje Tashi, Jin Zhang, Lobsang Yeshi, Lei Li, Nyima Tashi, Jingye Cai   +11 more
wiley   +1 more source