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Modernizing GNSS data acquisition, pre-processing, and distribution at volcanological observatories

P. Sakic, P. Boissier, P. Boissier, J.-M. Saurel et al. • Geoscientific Instrumentation, Methods and Data Systems (2026)

In recent years, the field of geodetic monitoring is undergoing a profound transformation driven by the transition from GPS-only positioning to a fully multi-GNSS environment. With Galileo, BeiDou, and modernized GPS & GLONASS constella...

DOAJ Open Access (DOAJ) DOI: 10.5194/gi-15-89-2026

<i>Escherichia coli</i> Optoelectronic Sensors for In Situ Monitoring of Selected Materials Across Water Supply Systems

Yonatan Uziel, Natan Orlov, Loay Atamneh, Offer Schwartsglass et al. • Chemosensors (2026)

Chemical monitoring of pollutants and hazardous materials in water supply systems traditionally depends on centralized laboratories, advanced instrumentation, and trained personnel, limiting accessibility and preventing real-time, on-site a...

DOAJ Open Access (DOAJ) DOI: 10.3390/chemosensors14030062

Assessment of Spatiotemporal Variations in the Water Quality of the Han River Basin, South Korea, Using Multivariate Statistical and APCS-MLR Modeling Techniques

Yong-Chul Cho, Hyeonmi Choi, Soon-Ju Yu, Sang-Hun Kim et al. • Agronomy (2021)

This study evaluated the spatiotemporal variability of water quality in the Han River Basin (HRB) as well as the contributions of potential pollution sources using multivariate statistical and absolute principal component score-multiple lin...

DOAJ Open Access (DOAJ) DOI: 10.3390/agronomy11122469

Moving from crisis response to a learning health system: Experiences from an Australian regional primary care network

Bianca Forrester, Georgia Fisher, Louise A. Ellis, Andrew Giddy et al. • Learning Health Systems (2025)

Abstract Introduction The COVID‐19 pandemic challenged primary care to rapidly innovate. In response, the Western Victorian Primary Health Network (WVPHN) developed a COVID‐19 online Community of Practice comprising general practitioners (G...

DOAJ Open Access (DOAJ) DOI: 10.1002/lrh2.10458

Neural Networks in Structural Engineering

R. Daniel VanLuchene, ROUFEI SUN • Computer-Aided Civil and Infrastructure Engineering (1990)

In the past few years literature on computational civil engineering has concentrated primarily on artificial intelligence (Al) applications involving expert system technology. This article discusses a different Al approach involving neural ...

OPENALEX cc-by-nc-nd DOI: https://doi.org/10.1111/j.1467-8667.1990.tb00377.x

Research on Prediction of Movable Fluid Percentage in Unconventional Reservoir Based on Deep Learning

Jiuxin Wang, Yutian Luo, Zhengming Yang, Xinli Zhao et al. • Applied Sciences (2021)

In order to improve the measurement speed and prediction accuracy of unconventional reservoir parameters, the deep neural network (DNN) is used to predict movable fluid percentage of unconventional reservoirs. The Adam optimizer is used in ...

DOAJ Open Access (DOAJ) DOI: 10.3390/app11083589