Ice-nucleating particles (INPs) enable ice formation, profoundly affecting the microphysical and radiative properties, lifetimes, and precipitation rates of clouds. Mineral dust emitted from arid regions, particularly potassium-containing feldspar (K-felds ...
Control design for robotic systems is complex and often requires solving an optimization to follow a trajectory accurately. Online optimization approaches like Model Predictive Control (MPC) have been shown to achieve great tracking performance, but requir ...
This study examines the impact of light absorption from biomass burning (BB) brown carbon (BrC) in the Mediterranean basin from local and distant fire incidents during a typical fire season in August 2019 and under severe fire activity in August 2021. The ...
Stable water isotopes (SWIs) contain valuable information on the past climate and phase changes in the hydrologic cycle. Recently, vapor measurements in the polar regions have provided new insights into the effects of snow-related and atmospheric processes ...
The Joint Photographic Experts Group (JPEG) AI learning-based image coding system is an ongoing joint standardization effort between International Organization for Standardization (ISO), International Electrotechnical Commission (IEC), and International Te ...
Soft actuators with a function of variable stiffness are beneficial to the improvement of the adaptability of robots, expanding the application areas and environments. We propose a tendon-driven soft bending actuator that can change its stiffness using fib ...
In this thesis, we explore techniques for addressing the communication bottleneck in data-parallel distributed training of deep learning models. We investigate algorithms that either reduce the size of the messages that are exchanged between workers, or th ...
This research investigates the robotic assembly of timber structures connected by wood–wood connections. As the digitization of the timber construction sector progresses, digital tools, such as industrial robotic arms and Computer Numerical Control machine ...
Bi-manual picking up of objects to toss them on a conveyor belt are dynamic manipulation activities generated daily in the industry. Such repetitive and physically demanding tasks are still done largely by humans for lack of similarly fast, precise, and ro ...
In this paper, we present an approach for learning a neural implicit signed distance function expressed in joint space coordinates, that efficiently computes distance-to-collisions for arbitrary robotic manipulator configurations. Computing such distances ...
