Representing Behaviour and Adaptation of Office Occupants in Building Simulation

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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 ...

Objective The study was undertaken to show the magnitude of interindividual differences in energy expenditure (i.e., heat production) under normal living conditions with the aim of providing physiological evidence to support the advancement of a personaliz ...

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 ...

The perception, physiology, behavior, and performance of building occupants are influenced by multi-domain exposures: the simultaneous presence of multiple environmental stimuli, i.e., visual, thermal, acoustic, and air quality. Despite being extensive, th ...

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 ...

Representing Behaviour and Adaptation of Office Occupants in Building Simulation

Chattez avec Graph Search

Memory of Motion for Initializing Optimization in Robotics

Using Machine Learning to Predict Mortality for COVID-19 Patients on Day 0 in the ICU

Application of UV absorbance and electron-donating capacity as surrogates for micropollutant abatement during full-scale ozonation of secondary-treated wastewater

Are green bonds priced lower than their conventional peers?

Interindividual variability of human thermoregulation: Toward personalized ergonomics of the indoor thermal environment

Mesh d-refinement: a data-based computational framework to account for complex material response

Large-scale traffic signal control and multimodal network design

Quality criteria for multi-domain studies in the indoor environment: Critical review towards research guidelines and recommendations

Multi-ion-sensing emulator and multivariate calibration optimization by machine learning models