Mitigating Slow Dynamics of Low-Cost Chemical Sensors for Mobile Air Quality Monitoring Sensor Networks

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Tightly-coupled sensor orientation, i.e. the simultaneous processing of temporal (GNSS and raw inertial) and spatial (image and lidar) constraints in a common adjustment, has demonstrated significant improvement in the quality of attitude determination wit ...

The p-Laplacian problem -del & sdot; ((mu + |del u|(p-2))del u) = f is considered, where mu is a given positive number. An anisotropic a posteriori residual-based error estimator is presented. The error estimator is shown to be equivalent, up to higher ord ...

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We perform an error analysis of a fully discretised Streamline Upwind Petrov Galerkin Dynamical Low Rank (SUPG-DLR) method for random time-dependent advection-dominated problems. The time integration scheme has a splitting-like nature, allowing for potenti ...

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Depleted Monolithic Active Pixel Sensor (DMAPS) sensors developed in the Tower Semiconductor 180 nm CMOS imaging process have been designed in the context of the ATLAS ITk upgrade Phase-II at the HL-LHC and for future collider experiments. The "MALTA-Czoch ...

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Human thermo-physiology models (HTPM) are useful tools to assess dynamic and non-uniform human thermal states. However, they are developed based on the physiological data of an average person. In this paper, we present a detailed evaluation of two sophisti ...

Mitigating Slow Dynamics of Low-Cost Chemical Sensors for Mobile Air Quality Monitoring Sensor Networks

Chattez avec Graph Search

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Partial discharge localization in power transformer tanks using machine learning methods

Health Prediction for Lithium-Ion Batteries Under Unseen Working Conditions

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Anisotropic Adaptive Finite Elements for a p-Laplacian Problem

Morphological and Material Programability of a Hall-Effect Based Soft Tactile Sensors

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Error estimates for SUPG-stabilised Dynamical Low Rank Approximations

Imaging sensor device using an array of single-photon avalanche diode photodetectors

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Statistical Inference for Inverse Problems: From Sparsity-Based Methods to Neural Networks

A Statistical Framework to Investigate the Optimality of Signal-Reconstruction Methods

Spatially adaptive machine learning models for predicting water quality in Hong Kong

MALTA-Cz: a radiation hard full-size monolithic CMOS sensor with small electrodes on high-resistivity Czochralski substrate

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Timing and spatial selection bias in rapid extreme event attribution

Multi-agent Learning with Privacy Guarantees

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Modeling local thermal responses of individuals: Validation of advanced human thermo-physiology models