Search results for "Data application"
showing 5 items of 5 documents
Model order effects on ICA of resting-state complex-valued fMRI data : application to schizophrenia
2018
Abstract Background Component splitting at higher model orders is a widely accepted finding for independent component analysis (ICA) of functional magnetic resonance imaging (fMRI) data. However, our recent study found that intact components occurred with subcomponents at higher model orders. New method This study investigated model order effects on ICA of resting-state complex-valued fMRI data from 82 subjects, which included 40 healthy controls (HCs) and 42 schizophrenia patients. In addition, we explored underlying causes for distinct component splitting between complex-valued data and magnitude-only data by examining model order effects on ICA of phase fMRI data. A best run selection me…
Exploring social media network landscape of post-Soviet space
2019
The “post-Soviet space” consists of countries with a substantial fraction of the world’s population; however, unlike many other regions, its social media network landscape is still somewhat under-explored. This paper aims at filling this gap. To this purpose, we use anonymized data on user friendships at VK.com (also known as VKontakte and, informally, as “Russian Facebook”), which is the largest and most popular social media portal in the post-Soviet space with hundreds of millions of user accounts. Using the VK network snapshots from October 2015 to December 2016, we conduct a “multiscale” empirical study of this network by considering conn…
A methodology to estimate forest fires burned areas and burn severity degrees using Sentinel-2 data. Application to the October 2017 fires in the Ibe…
2021
Abstract A methodology to estimate the extent of areas affected by forest fires, as well as the burn severity levels using Sentinel 2 images (10 and 20 m) is proposed and applied to the fires occurred in October 2017 in Spain and Portugal. An extension larger than 250,000 ha and 4 burn severity levels (low, moderate, high and very high) have been obtained. The comparison with the European Forest Fire Information System (EFFIS), which uses MODIS images (250 m), shows that the methodology improves the area estimate by 10 % in commission area. In terms of burn severity levels, the Separability index (SI) and the Kappa statistic (k) show a high correlation between Sentinel-2 and EFFIS (SI value…
Measuring the Rate of Information Transfer in Point-Process Data: Application to Cardiovascular Interactions
2021
We present the implementation to cardiovascular variability of a method for the information-theoretic estimation of the directed interactions between event-based data. The method allows to compute the transfer entropy rate (TER) from a source to a target point process in continuous time, thus overcoming the severe limitations associated with time discretization of event-based processes. In this work, the method is evaluated on coupled cardiovascular point processes representing the heartbeat dynamics and the related peripheral pulsation, first using a physiologically-based simulation model and then studying real point-process data from healthy subjects monitored at rest and during postural …
Assessing uncertainty of voter transitions estimated from aggregated data. Application to the 2017 French presidential election
2020
[EN] Inferring electoral individual behaviour from aggregated data is a very active research area, with ramifications in sociology and political science. A new approach based on linear programming is proposed to estimate voter transitions among parties (or candidates) between two elections. Compared to other linear and quadratic programming models previously published, our approach presents two important innovations. Firstly, it explicitly deals with new entries and exits in the election census without assuming unrealistic hypotheses, enabling a reasonable estimation of vote behaviour of young electors voting for the first time. Secondly, by exploiting the information contained in the model…