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Jianxiang Wang

Biographic Data

ID8074320
NAMEJianxiang Wang
GIVEN NAMESJianxiang
FAMILY NAMEWang
SIGNATUREWANG J
AFFILIATIONSChongqing University of Posts and Telecommunications
ORCID0009-0009-6021-7555
VERIFIEDYes
TOTAL WORKS3
TOTAL CITATIONS0
AUTHOR COUNT3
EDITOR COUNT0
FIRST PUBLICATION YEAR2024
LATEST PUBLICATION YEAR2026
H-INDEX0
  • Effectiveness of LEARNS model-based health education on health literacy and self-management capabilities in patients with pneumoconiosis

    Open Access•Meirui Liu, Baoping Li et al.•ARTICLE•Frontiers in Public Health•2026

    Objectives To evaluate the effect of LEARNS model-based health education for patients with pneumoconiosis. Study design A randomized controlled trial with repeated measures design was conducted. A total of 120 patients with stable pneumoconiosis were randomly assigned to either a control group ( n = 60) receiving conventional treatment or an intervention group ( n = 60) receiving conventional treatment plus LEARNS model-based health education. Me…

  • VST-Pca

    Open Access•Minghao Liu, Qingxi Luo et al.•ARTICLE•ISPRS International Journal of…•2024

    Land use/cover change (LUCC) refers to the phenomenon of changes in the Earth’s surface over time. Accurate prediction of LUCC is crucial for guiding policy formulation and resource management, contributing to the sustainable use of land, and maintaining the health of the Earth’s ecosystems. LUCC is a dynamic geographical process involving complex spatiotemporal dependencies. Existing LUCC simulation models suffer from insufficient spatiotemporal…

  • Simulating Urban Expansion from the Perspective of Spatial Anisotropy and Expansion Neighborhood

    Open Access•Minghao Liu, Jianxiang Wang et al.•ARTICLE•ISPRS International Journal of…•2024

    Exploring spatial anisotropy features and capturing spatial interactions during urban change simulation is of great significance to enhance the effectiveness of dynamic urban modeling and improve simulation accuracy. Addressing the inadequacies of current cellular automaton-based urban expansion models in exploring spatial anisotropy features, overlooking spatial interaction forces, and the ineffective expansion of cells due to traditional neighb…

No prominent works on this page.

  • VST-Pca

    Open Access•Minghao Liu, Qingxi Luo et al.•ARTICLE•ISPRS International Journal of…•2024

    Land use/cover change (LUCC) refers to the phenomenon of changes in the Earth’s surface over time. Accurate prediction of LUCC is crucial for guiding policy formulation and resource management, contributing to the sustainable use of land, and maintaining the health of the Earth’s ecosystems. LUCC is a dynamic geographical process involving complex spatiotemporal dependencies. Existing LUCC simulation models suffer from insufficient spatiotemporal…

  • Simulating Urban Expansion from the Perspective of Spatial Anisotropy and Expansion Neighborhood

    Open Access•Minghao Liu, Jianxiang Wang et al.•ARTICLE•ISPRS International Journal of…•2024

    Exploring spatial anisotropy features and capturing spatial interactions during urban change simulation is of great significance to enhance the effectiveness of dynamic urban modeling and improve simulation accuracy. Addressing the inadequacies of current cellular automaton-based urban expansion models in exploring spatial anisotropy features, overlooking spatial interaction forces, and the ineffective expansion of cells due to traditional neighb…

  • Effectiveness of LEARNS model-based health education on health literacy and self-management capabilities in patients with pneumoconiosis

    Open Access•Meirui Liu, Baoping Li et al.•ARTICLE•Frontiers in Public Health•2026

    Objectives To evaluate the effect of LEARNS model-based health education for patients with pneumoconiosis. Study design A randomized controlled trial with repeated measures design was conducted. A total of 120 patients with stable pneumoconiosis were randomly assigned to either a control group ( n = 60) receiving conventional treatment or an intervention group ( n = 60) receiving conventional treatment plus LEARNS model-based health education. Me…

Civil engineering (2 works) · Engineering (2 works) · Land Use and Ecosystem Services (2 works) · Remote Sensing and Land Use (2 works) · Anisotropy (1 works) · Artificial Intelligence (1 works) · Chemistry (1 works) · Chromatography (1 works) · Computer Science (1 works) · Data mining (1 works)

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