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A 30-year phenological study of mangrove forests at the species level as a function of climatic drivers using multispectral remote sensing satellites
Eigenvector Spatial Filtering Enhancing Natural Hazards Vulnerability Assessment in a Susceptible Urban Environment: A Case Study of Izmir Earthquake in Turkey
Synthesis of MgAl2O4: Eu3+ Nano-phosphors through the Use of Aniline and Hydrazine Fuels: Study of Structural and Optical Characteristics through Calcination
Modeling and assessment of a hybrid pyramid solar still-humidification-dehumidification desalination system for sustainable freshwater production in SWGHs: A case study
Numerical study and controlled generation of double emulsion droplet in a six-way junction microfluidic device using design of experiment method
A Comparative Analysis of Machine Learning Models for Predicting Groundwater and Surface Water in a Stressed Semi-Arid Watershed: The Khanmirza Case Study
Comparison of kriging methods in rainfall estimation based on entropy‑copula (case study: Simineh river, lake Urmia Basin, Iran)
Evaluating the Performance of Soil and Water Assessment Tool SWAT) in a Snow-Dominated Climate (Case Study: Azna–Aligoudarz Basin, Iran)
Innovative FRP shear strengthening of RC structural walls using EBROG method and FRP spike anchors: An experimental and theoretical study
A game-theoretic approach to sustainable smart manufacturing using IoT under policy incentives: a case study of Iran and South Korea
A 30-year phenological study of mangrove forests at the species level as a function of climatic drivers using multispectral remote sensing satellites
A 30-year phenological study of mangrove forests at the species level as a function of climatic drivers using multispectral remote sensing satellites
Direct numerical simulation of flow around two non-identical tandem cylinders: Study of secondary wake transition and flow structure
Predicting Rock Hardness Using Measurement While Drilling (MWD) Data in a Case Study of Rotary Drilling in an Open-Pit Mine
A comparative analysis of machine learning models for predicting groundwater and surface water in a stressed semi-arid watershed: The Khanmirza case study