In essence, targeting mineralization necessitates exact structural delineation and thorough
lithological map**. The latter is still a challenge for geologists and its lack hinders …

The thermochemical conversion of biomass is a promising technology due to its cost-
effectiveness and feedstock flexibility, with pyrolysis being a particularly noteworthy method …

Ensemble learning techniques have achieved state-of-the-art performance in diverse
machine learning applications by combining the predictions from two or more base models …

Breast cancer death rates are higher than any other cancer in American women. Machine
learning-based predictive models promise earlier detection techniques for breast cancer …

The accurate map** of crop types is crucial for ensuring food security. Remote Sensing
(RS) satellite data have emerged as a promising tool in this field, offering broad spatial …

Solar power integration in electrical grids is complicated due to dependence on volatile
weather conditions. To address this issue, continuous research and development is required …

The preparation process of biomass-based biochar materials is usually screened using
traditional trial-and-error experiments. In this approach, the electrochemical properties of …

The identification of land use/land cover (LULC) changes is important for monitoring,
evaluating, and preserving natural resources. In the Kurdistan region, the utilization of …

Accurate aboveground biomass (AGB) estimations over large areas are essential for
assessing carbon stocks and forest resources. This study evaluated machine learning …

Predictive maintenance harnesses statistical analysis to preemptively identify equipment
and system faults, facilitating cost-effective preventive measures. Machine learning …