Thermal Conditions in Indoor Environments: Exploring the Reasoning behind Standard-Based Recommendations

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Taking a step back from glass towers facades to make them compatible with the 2050 targets

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Skyscrapers or glass towers are an extremely common model throughout the world. In the current context of climate change and resource depletion, we need to develop new postures towards these objects, especially for existing buildings that are becoming obso ...

2023

DIET Controller: Dynamic Indoor Environment using Deep Reinforcement Learning

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Heating, Ventilation, and Air Conditioning (HVAC) Systems utilize much energy, accounting for 40% of total building energy use. The temperatures in buildings are commonly held within narrow limits, leading to higher energy use. Measurements from office bui ...

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 ...

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Search for dark photon decays to μ+μ- at NA62

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The NA62 experiment at CERN, designed to study the ultra-rare decay K+ -> pi(+) nu(nu) over bar, has also collected data in beam-dump mode. In this configuration, dark photons may be produced by protons dumped on an absorber and reach a decay volume beginn ...

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When do Minimax-fair Learning and Empirical Risk Minimization Coincide?

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Minimax-fair machine learning minimizes the error for the worst-off group. However, empirical evidence suggests that when sophisticated models are trained with standard empirical risk minimization (ERM), they often have the same performance on the worst-of ...

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Learning Transformations To Reduce the Geometric Shift in Object Detection

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The performance of modern object detectors drops when the test distribution differs from the training one. Most of the methods that address this focus on object appearance changes caused by, e.g., different illumination conditions, or gaps between syntheti ...

Ieee Computer Soc2023

RECA: A Multi-Task Deep Reinforcement Learning-Based Recommender System for Co-Optimizing Energy, Comfort and Air Quality in Commercial Buildings

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We present the design and implementation of RECA, a novel human-centric recommender system for co-optimizing energy consumption, comfort and air quality in commercial buildings. Existing works generally optimize these objectives separately, or by only cont ...

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Influence of outdoor air pollution on European residential ventilative cooling potential

Dusan Licina, Evangelos Belias

Residential ventilative cooling via natural ventilation is influenced by outdoor air pollution. However, relative to climate, outdoor air pollution is not comprehensively considered in determining the ventilative cooling potential of buildings. To assess t ...

ELSEVIER SCIENCE SA2023

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Taking a step back from glass towers facades to make them compatible with the 2050 targets

Sergi Aguacil Moreno, Bernard Paule

2023

DIET Controller: Dynamic Indoor Environment using Deep Reinforcement Learning

Arnab Chatterjee

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

RECA: A Multi-Task Deep Reinforcement Learning-Based Recommender System for Co-Optimizing Energy, Comfort and Air Quality in Commercial Buildings

Andrew James Sonta

Association for Computing Machinery2023