The objective of this study is to quantify the role of climate and human impacts on streamflow
conditions by using historical streamflow records, in conjunction with trend analysis and …

For climate change impact studies, bias correction methods are widely utilized to improve
climate model outputs by correcting the representation of climate variables. In addition to the …

Since assembly tasks are frequently performed in a wide range of industries, there have
been many efforts to develop robotic assembly strategies. However, robotic assembly is only …

Despite wide use of regression-based regional flood frequency analysis (RFFA) methods,
the majority are based on either ordinary least squares (OLS) or generalized least squares (…

Recently, robot learning through deep reinforcement learning has incorporated various robot
tasks through deep neural networks, without using specific control or recognition algorithms…

Accurate and reliable hydrological forecasts play a pivotal role in ensuring water security,
facilitating flood preparedness, and supporting agriculture activities. This study investigates the …

This study presents the potential of hydrological ensemble forecasts over South Korea for
medium-range forecast lead times (1–7 days). To generate hydrological forecasts, this study …

Numerous data-driven models have been introduced to establish reliable predictions in the
rainfall-runoff relationship. The majority of these models are trained using a supervised …

Frequency analysis of streamflow provides an essential ingredient in our understanding of
hydrologic events and provides needed guidance in the design and management of water …

If a collaborative robot can measure contact force when in contact with the environment or
humans, it can achieve better performance on collision detection, hand guiding, and force …