Herein, machine learning (ML) models using multiple linear regression (MLR), support vector regression (SVR), random forest (RF) and artificial neural network (ANN) are developed and compared to predict the output features viz. specific capacitance (Csp), ...
In light of the challenges posed by climate change and the goals of the Paris Agreement, electricity generation is shifting to a more renewable and decentralized pattern, while the operation of systems like buildings is increasingly electrified. This calls ...
Climate change is expected to alter the temporal distribution of precipitation events, leading to prolonged drought periods and an increased frequency of extreme precipitation events. Changes in precipitation pattern will directly affect soil moisture dyna ...
As air temperature and vapor pressure deficit (VPD) increase continuously, forests are losing more water through evapotranspiration, with large consequences for local and global hydrological cycles. In regions with high vegetation cover, soil warming can b ...
Despite their high ecological value, non-perennial streams have received less attention than their perennial counterparts. This doctoral thesis addresses this disparity by advancing knowledge on the dynamics of the drainage density and hydrologic processes ...
The upcoming Square Kilometre Array Observatory will produce images of neutral hydrogen distribution during the epoch of reionization by observing the corresponding 21-cm signal. However, the 21-cm signal will be subject to instrumental limitations such as ...
Plant water uptake from the soil is a crucial element of the global hydrological cycle and essential for vegetation drought resilience. Yet, knowledge of how the distribution of water uptake depth (WUD) varies across species, climates, and seasons is scarc ...
In the rapidly evolving landscape of machine learning research, neural networks stand out with their ever-expanding number of parameters and reliance on increasingly large datasets. The financial cost and computational resources required for the training p ...
We propose a novel approach to evaluating the ionic Seebeck coefficient in electrolytes from relatively short equilibrium molecular dynamics simulations, based on the Green-Kubo theory of linear response and Bayesian regression analysis. By exploiting the ...
Assessing the individual risk of Major Adverse Cardiac Events (MACE) is of major importance as cardiovascular diseases remain the leading cause of death worldwide. Quantitative Myocardial Perfusion Imaging (MPI) parameters such as stress Myocardial Blood F ...
