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Sick Building Syndrome and Building Characteristics

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Efficacy of temporal and spatial abstraction for training accurate machine learning models: A case study in smart thermostats

Rachid Guerraoui, Alexandre David Olivier Maurer, Omid Ardakanian

Smart thermostats are increasingly popular in homes and buildings as they improve occupant comfort, lower energy use in heating and cooling systems, and reduce utility bills by automatically adjusting room temperature according to measurements of their bui ...

ELSEVIER SCIENCE SA2023

Data for: "A Neural-Network-Based Convex Regularizer for Inverse Problems"

Michaël Unser, Pakshal Narendra Bohra, Alexis Marie Frederic Goujon, Sebastian Jonas Neumayer, Stanislas Ducotterd

Data for: "A Neural-Network-Based Convex Regularizer for Inverse Problems". The corresponding scripts can be accessed on GitHub (https://github.com/axgoujon/convex_ridge_regularizers). The data is organized as follows: - ct_data_sets.tar.gz: contains prepr ...

Zenodo2023

Optimal digital filter selection for remote photoplethysmography (rPPG) signal conditioning

Ata Jedari Golparvar

Remote photoplethysmography (rPPG) using camera-based imaging has shown excellent potential recently in vital signs monitoring due to its contactless nature. However, the optimum filter selection for pre-processing rPPG data in signal conditioning is still ...

IOP Publishing Ltd2023

Housing, street and health: a new systemic research framework

Paola Viganò, Stéphane Joost, Dusan Licina, Anna Pagani, Valentin Daniel Maurice Bourdon, Mathias Lerch, Catarina Wall Gago, Derek Pierre Christie, Idris Guessous

As the world’s population grows in cities, urban dwellers spend a large amount of time inside their home, making housing health ever more important. Critical for residents’ health, the interactions between indoor residential environments and outdoor enviro ...

2023

Ultrabroadband sound control with deep-subwavelength plasmacoustic metalayers

Romain Christophe Rémy Fleury, Hervé Lissek, Stanislav Sergeev

Controlling audible sound requires inherently broadband and subwavelength acoustic solutions, which are to date, crucially missing. This includes current noise absorption methods, such as porous materials or acoustic resonators, which are typically ineffic ...

Nature Research2023

Functional data analysis with rough sample paths?

Victor Panaretos, Neda Mohammadi Jouzdani

Functional data are typically modeled as sample paths of smooth stochastic processes in order to mitigate the fact that they are often observed discretely and noisily, occasionally irregularly and sparsely. The smoothness assumption is imposed to allow for ...

TAYLOR & FRANCIS LTD2024

Model-based constraints for trajectory determination of quad-copters: Design, calibration & merits for direct orientation

Jan Skaloud, Davide Antonio Cucci, Kenneth Joseph Paul

This paper proposes a novel method to improve georeferencing of airborne laser scanning by improved trajectory estimation using Vehicle Dynamic Model. In Vehicle Dynamic Model (VDM), the relationship between the dynamics of the platform and control inputs ...

2023

Universal and adaptive methods for robust stochastic optimization

Ali Kavis

Within the context of contemporary machine learning problems, efficiency of optimization process depends on the properties of the model and the nature of the data available, which poses a significant problem as the complexity of either increases ad infinit ...

EPFL2023

Toward contactless human thermal monitoring: A framework for Machine Learning-based human thermo-physiology modeling augmented with computer vision

Alexandre Massoud Alahi, Dolaana Khovalyg, Mohamed Ossama Ahmed Abdelfattah, Mohamad Rida

The transition towards a human-centered indoor climate is beneficial from occupants’ thermal comfort and from an energy reduction perspective. However, achieving this goal requires the knowledge of the thermal state of individuals at the level of body part ...

2023

Human personal air pollution clouds in a naturally ventilated office during the COVID-19 pandemic

Dusan Licina, Shen Yang, Maria Viviana Gonzalez Serrano, Akila Muthalagu

Personal cloud, termed as the difference in air pollutant concentrations between breathing zone and room sites, represents the bias in approximating personal inhalation exposure that is linked to accuracy of health risk assessment. This study performed a t ...

PERGAMON-ELSEVIER SCIENCE LTD2023

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Model-based constraints for trajectory determination of quad-copters: Design, calibration & merits for direct orientation

Jan Skaloud, Davide Antonio Cucci, Kenneth Joseph Paul

2023

Universal and adaptive methods for robust stochastic optimization

Ali Kavis

EPFL2023

Toward contactless human thermal monitoring: A framework for Machine Learning-based human thermo-physiology modeling augmented with computer vision

Alexandre Massoud Alahi, Dolaana Khovalyg, Mohamed Ossama Ahmed Abdelfattah, Mohamad Rida

2023

Human personal air pollution clouds in a naturally ventilated office during the COVID-19 pandemic

Dusan Licina, Shen Yang, Maria Viviana Gonzalez Serrano, Akila Muthalagu

PERGAMON-ELSEVIER SCIENCE LTD2023

Efficacy of temporal and spatial abstraction for training accurate machine learning models: A case study in smart thermostats

Rachid Guerraoui, Alexandre David Olivier Maurer, Omid Ardakanian

ELSEVIER SCIENCE SA2023