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Microsoft Office

Related publications (36)

Generalization and Personalization of Machine Learning for Multimodal Mobile Sensing in Everyday Life

A range of behavioral and contextual factors, including eating and drinking behavior, mood, social context, and other daily activities, can significantly impact an individual's quality of life and overall well-being. Therefore, inferring everyday life aspe ...

EPFL2024

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

Dusan Licina, Shen Yang, 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

A New Representation Framework for View-Out Research

Yunjoung Cho

To address the current gap in view-out research, this study aims to develop a workflow able to accurately capture dynamic views in an experimental setting. In testing the suitability of the proposed methodology, we conducted two comparative studies on the ...

2023

Optimal sensor placement for personal inhalation exposure detection in static and dynamic office environments

Dusan Licina, Seoyeon Yun

Modern health and productivity concerns related to air pollutant exposure in buildings have sparked the need for occupant-centric monitoring and ventilation control. The existing personal exposure monitoring is often restricted to stationary air quality se ...

PERGAMON-ELSEVIER SCIENCE LTD2023

Impact of dynamic lighting control on light exposure, visual comfort and alertness in office users

Jean-Louis Scartezzini, Mirjam Münch, Ali Motamed, Marta Benedetti, Lenka Maierova

The lighting environment at indoor workplaces is important not only to provide vision and visual comfort, but also for light's direct influence on human physiology, cognitive performance and mood. The purpose of this ongoing study is to investigate the imp ...

IOP Science2019

The current trend for deep learning has come with an enormous computational need for billions of Multiply-Accumulate (MAC) operations per inference. Fortunately, reduced precision has demonstrated large benefits with low impact on accuracy, paving the way ...

IEEE2019

HideMyApp: Hiding the Presence of Sensitive Apps on Android

Jean-Pierre Hubaux, John Stephan, Kévin Clément Huguenin, Italo Ivan Dacosta Petrocelli, Thi Van Anh Pham, Eleonora Losiouk

Millions of users rely on mobile health (mHealth) apps to manage their wellness and medical conditions. Although the popularity of such apps continues to grow, several privacy and security challenges can hinder their potential. In particular, the simple fa ...

Proceedings of the 28th USENIX Security Symposium2019

HideMyApp : Hiding the Presence of Sensitive Apps on Android

Jean-Pierre Hubaux, John Stephan, Kévin Clément Huguenin, Italo Ivan Dacosta Petrocelli, Thi Van Anh Pham, Eleonora Losiouk

2019

HideMyApp : Hiding the Presence of Sensitive Apps on Android

Jean-Pierre Hubaux, John Stephan, Kévin Clément Huguenin, Italo Ivan Dacosta Petrocelli, Eleonora Losiouk

USENIX ASSOC2019

Understanding building occupant activities at scale: An integrated knowledge-based and data-driven approach

Andrew James Sonta

Buildings are our homes and our workplaces. They directly affect our well-being, and they impact the natural global environment primarily through the energy they consume. Understanding the behavior of occupants in buildings has vital implications for impro ...

2018

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