Publications associées à Inferring competitive role patterns in reality TV show through nonverbal analysis

Orchestrating chromosome conformation capture analysis with Bioconductor

Genome-wide chromatin conformation capture assays provide formidable insights into the spatial organization of genomes. However, due to the complexity of the data structure, their integration in multi-omics workflows remains challenging. We present data st ...

Nature Research2024

Data set for control of Ge island coalescence for the formation of nanowires on silicon

Alok Rudra, Anna Fontcuberta i Morral, Sara Marti Sanchez, Santhanu Panikar Ramanandan, Joel René Sapera, Vladimir Dubrovskii

This document contains all the data and the details of the analysis used in the manuscript titled " Control of Ge island coalescence for the formation of nanowires on silicon." https://doi.org/10.1039/D3NH00573A ...

EPFL Infoscience2024

Multiscale pattern analysis of building replacements in Zurich from 2000 to 2019

Corentin Jean Dominique Fivet, Jingxian Ye

Building replacement (BR) – i.e., the demolition of existing structures and subsequent construction of new buildings on the same site – is often understood as a necessary urban planning strategy despite significant environmental implications regarding soli ...

2023

Tumescense monitoring system for diagnosing erectile dysfunction and methods of use

Nikolaos Stergiopoulos, Rodrigo Araujo Fraga Da Silva

Systems and methods for monitoring penile tumescence are provided that overcome the drawbacks of previously known systems by providing a wearable formed of a flexible and elastic tube having a plurality of sensors disposed on or embedded within it, the wea ...

2023

Toward a common standard for data and specimen provenance in life sciences

Marco Mattavelli, Anna Marsano

Open and practical exchange, dissemination, and reuse of specimens and data have become a fundamental requirement for life sciences research. The quality of the data obtained and thus the findings and knowledge derived is thus significantly influenced by t ...

WILEY2023

Toward data-driven materials design: From atoms to pilot plants

Kevin Maik Jablonka

Discovering new materials is essential but challenging, time-consuming, and expensive. In many cases, simulations can be useful for estimating material properties. For many of the most interesting properties, however, simulations are infeasible because of ...

EPFL2023

A Wearable Smart Glove and Its Application of Pose and Gesture Detection to Sign Language Classification

Josephine Anna Eleanor Hughes

Advances in soft sensors coupled with machine learning are enabling increasingly capable wearable systems. Since hand motion in particular can convey useful information for developing intuitive interfaces, glove-based systems can have a significant impact ...

Institute of Electrical and Electronics Engineers Inc.2022

Basin-scale gyres and mesoscale eddies in large lakes: A novel procedure for their detection and characterization, assessed in Lake Geneva

Ulrich Lemmin, David Andrew Barry, Mehrshad Foroughan, Frédéric Charles Soulignac, Seyed Mahmood Hamze Ziabari

In large lakes subject to the Coriolis force, basin-scale gyres and mesoscale eddies, i.e. rotating coherent water masses, play a key role in spreading biochemical materials and energy throughout the lake. In order to assess the spatial and temporal extent ...

2022

Geoinformation Harvesting From Social Media Data: A community remote sensing approach

Devis Tuia, Alex Hubertus Levering

As unconventional sources of geoinformation, massive imagery and text messages from open platforms and social media form a temporally quasi-seamless, spatially multiperspective stream, but with unknown and diverse quality. Due to its complementarity to rem ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022

The role of convolutional neural networks in scanning probe microscopy: a review

Georg Fantner

Progress in computing capabilities has enhanced science in many ways. In recent years, various branches of machine learning have been the key facilitators in forging new paths, ranging from categorizing big data to instrumental control, from materials desi ...

BEILSTEIN-INSTITUT2021

Measuring and modeling the motor system with machine learning

Mackenzie Mathis, Alexander Mathis, Alessandro Marin Vargas

The utility of machine learning in understanding the motor system is promising a revolution in how to collect, measure, and analyze data. The field of movement science already elegantly incorporates theory and engineering principles to guide experimental w ...

2021

Modeling Compact Intracloud Discharge (CID) as a Streamer Burst

Farhad Rachidi-Haeri, Marcos Rubinstein

Narrow Bipolar Pulses are generated by bursts of electrical activity in the cloud and these are referred to as Compact Intracloud Discharges (CID) or Narrow Bipolar Events in the current literature. These discharges usually occur in isolation without much ...

2020

Modern Schools in Angola, 1961-1975: Design with Climate and Heritage

Maria Margarida Gonçalves Quintã

The architectural production of Angola between 1961 and 1975 forms the basis of the current study. Taking into consideration that buildings' environmental performance is, at one time, one of the most central aspects of the Modern Movement legacy and a pres ...

EPFL2019

Graph Signal Processing for Machine Learning: A Review and New Perspectives

Pascal Frossard, Ntorina Thanou, Xiaowen Dong, Laura Toni, Michael Bronstein

The effective representation, processing, analysis, and visualization of large-scale structured data, especially those related to complex domains, such as networks and graphs, are one of the key questions in modern machine learning. Graph signal processing ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2020

Comparison of autofluorescence and white-light bronchoscopies performed with the Evis Lucera Spectrum for the detection of bronchial cancers: a meta-analysis

Georges Wagnières, Xiuwei Zhang, Li Wang, Yang Yang

Background: Many recent studies have reported that autofluorescence bronchoscopy (AFB) has a superior sensitivity and decreased specificity in the diagnosis of bronchial cancers when compared with white-light bronchoscopy (WLB). We specifically analyzed th ...

AME PUBL CO2020

MedCo(2): Privacy-Preserving Cohort Exploration and Analysis

Jean-Pierre Hubaux, Mickaël Misbach, David Jules Froelicher, Jean Louis Raisaro, Juan Ramón Troncoso-Pastoriza

Medical studies are usually time consuming, cumbersome and extremely costly to perform, and for exploratory research, their results are also difficult to predict a priori. This is particularly the case for rare diseases, for which finding enough patients i ...

IOS PRESS2020

Data for Urban Scale Building Energy Modelling: Assessing Impacts and Overcoming Availability Challenges

François Maréchal, Solène Goy

Data are essential to urban building energy models and yet, obtaining sufficient and accurate building data at a large-scale is challenging. Previous studies have highlighted that the data impact on urban case studies has not been sufficiently discussed. T ...

2020

Crowdbreaks: Tracking Health Trends Using Public Social Media Data and Crowdsourcing

Martin Guillermo Mueller, Marcel Salathé

In the past decade, tracking health trends using social media data has shown great promise, due to a powerful combination of massive adoption of social media around the world, and increasingly potent hardware and software that enables us to work with these ...

2019

Social Sensing Methods for Analysis of Dyadic Hospitality Encounters

Skanda Muralidhar

First impressions are critical to professional interactions, especially in service industry like hospitality. In the service industry, customers often assess quality of service based on the behavior, perceived personality, and other attributes of the front ...

EPFL2019

Two-Tier Mapper, an unbiased topology-based clustering method for enhanced global gene expression analysis

Kathryn Hess Bellwald, Cathrin Brisken, Jacques Rougemont, Rachel Marcone

Motivation: Unbiased clustering methods are needed to analyze growing numbers of complex data sets. Currently available clustering methods often depend on parameters that are set by the user, they lack stability, and are not applicable to small data sets. ...

2019