Many robotics problems are formulated as optimization problems. However, most optimization solvers in robotics are locally optimal and the performance depends a lot on the initial guess. For challenging problems, the solver will often get stuck at poor loc ...
Rationale: Given the expanding number of COVID-19 cases and the potential for new waves of infection, there is an urgent need for early prediction of the severity of the disease in intensive care unit (ICU) patients to optimize treatment strategies.Objecti ...
Ozonation of secondary-treated wastewater for the abatement of micropollutants requires a reliable control of ozone doses. Changes in the UV absorbance of dissolved organic matter (DOM) during ozonation allow to estimate micropollutant abatement on-line an ...
The green bond market's rapid growth has alerted issuers and investors to this sustainable area of investment. This study ascertains whether green bonds are priced lower than conventional bonds-whether a negative green bond premium exists in both Chinese a ...
Model-free data-driven computational mechanics (DDCM) is a new paradigm for simulations in solid mechanics. The modeling step associated to the definition of a material constitutive law is circumvented through the introduction of an abstract phase space in ...
Traffic congestion constitutes one of the most frequent, yet challenging, problems to address in the urban space. Caused by the concentration of population, whose mobility needs surpass the serving capacity of urban networks, congestion cannot be resolved ...
One paramount challenge in multi-ion-sensing arises from ion interference that degrades the accuracy of sensor calibration. Machine learning models are here proposed to optimize such multivariate calibration. However, the acquisition of big experimental da ...
