Éditeur(s) : HAL CCSD Elsevier
Résumé : International audience
The tropical to warm-temperate marine brown macroalgal genus Lobophora (Dictyotales, Phaeophyceae) recently drew attention because of its striking regional diversity. In this study we reassess Lobophora global species diversity, and species distributions, and explore how historical factors have shaped current diversity patterns. We applied a series of algorithmic species delineation techniques on a global mitochondrial cox3 dataset of 598 specimens, resulting in an estimation of 98–121 species. This diversity by far exceeds traditional diversity estimates based on morphological data. A multi-locus time-calibrated species phylogeny using a relaxed molecular clock, along with DNA-confirmed species distribution data was used to analyse ancestral area distributions, dispersal-vicariance-founder events, and temporal patterns of diversification under different biogeographical models. The origin of Lobophora was estimated in the Upper Cretaceous (−75 to −60 MY), followed by gradual diversification until present. While most speciation events were inferred within marine realms, founder events also played a non-negligible role in Lobophora diversification. The Central Indo-Pacific showed the highest species diversity as a result of higher speciation events in this region. Most Lobophora species have small ranges limited to marine realms. Lobophora probably originated in the Tethys Sea and dispersed repeatedly in the Atlantic (including the Gulf of Mexico) and Pacific Oceans. The formation of the major historical marine barriers (Terminal Tethyan event, Isthmus of Panama, Benguela upwelling) did not act as important vicariance events. Long-distance dispersal presumably represented an important mode of speciation over evolutionary time-scales. The limited geographical ranges of most Lobophora species, however, vouch for the rarity of such events.
ISSN: 1055-7903

hal-01535635
http://hal.upmc.fr/hal-01535635
http://hal.upmc.fr/hal-01535635/document
http://hal.upmc.fr/hal-01535635/file/Vieira_2017_Historical.pdf
DOI : 10.1016/j.ympev.2017.03.007

Éditeur(s) : HAL CCSD American Geophysical Union (AGU)
Résumé : International audience
Nowadays, technological advances in satellite imagery measurements as well as the development of dense geodetic and seismologic networks allow for a detailed analysis of surface deformation associated with active fault seismic cycle. However, the study of earthquake dynamics faces several limiting factors related to the difficulty to access the deep source of earthquake and to integrate the characteristic time scales of deformation processes that extend from seconds to thousands of years. To overcome part of these limitations and better constrain the role and couplings between kinematic and mechanical parameters, we have developed a new experimental approach allowing for the simulation of strike-slip fault earthquakes and analyze in detail hundreds of successive seismic cycle. Model rheology is made of multilayered visco-elasto-plastic analog materials to account for the mechanical behavior of the upper and lower crust and to allow simulating brittle/ductile coupling, postseismic deformation phase and far-field stress transfers. The kinematic evolution of the model surface is monitored using an optical system, based on subpixel spectral correlation of high-resolution digital images. First, results show that the model succeed in reproducing the deformation mechanisms and surface kinematics associated to the main phases of the seismic cycle indicating that model scaling is satisfactory. These results are comforted by using numerical algorithms to study the strain and stress distribution at the surface and at depth, along the fault plane. Our analog modeling approach appears, then, as an efficient complementary approach to investigate earthquake dynamics.
ISSN: 0278-7407

hal-01174176
https://hal.archives-ouvertes.fr/hal-01174176
DOI : 10.1002/2014TC003701

Éditeur(s) : HAL CCSD AGU and the Geochemical Society
Résumé : International audience
We propose a new thermomechanical numerical model of mid-ocean ridge accretion aimed at investigating asymmetric spreading rates, diverse configurations of lens and sill magma injections, crystallization and depth, and on- and off-axis patterns of hydrothermal cooling. The numerical algorithm iteratively resolves temperature and motion equations until it reaches a stationary solution. The motion equation was written in a vorticity-stream function formalism, with boundary and internal conditions applied to the stream function to impose the style of magma injection. Unlike in previous models, our model does not assume an a priori shape for the temperature field, which is initiated by an initial half-space cooling according to the left and right spreading rates. Complex patterns of hydrothermal cooling are simulated by enhanced thermal diffusivity. The model succeeds in describing the dynamic and thermal effects of spreading rates, the style of magma intrusion, and the hydrothermal cooling. Accurate descriptions of these are essential to study the cooling histories of crustal rocks and geophysical observables.
ISSN: 1525-2027

hal-00413118
https://hal.archives-ouvertes.fr/hal-00413118
DOI : 10.1029/2008GC002270

Éditeur(s) : HAL CCSD
Résumé : International audience
“Affective Computing is computing that relates to, arises from, or deliberately influences emotions” (R.W. Picard, MIT Press, 1997). Specifically, psychosocial equilibrium is now considered as a major issue for both individual and public health. Predicting human emotions via non-intrusive methods is a great challenge triggered by the rise of intelligent assisting systems. In order to determine the emotional state of a subject having a potential psychosocial disorder, it is required to process both neutral and expressive emotions. A computer-engineered method aiming to provide emotional information from videos is proposed. An original approach for affect classification and its interpretation is presented.The database is part of the HUMAINE database, and consists of a large volume of video clips, each displaying individuals, depressed or not, talking with a conversational agent. Both the high-dimensionality of data and its temporal aspect require a pre-training that consists of cleaning, sorting and feature selection, in order to make relevant information usable for further processing by MachineLearning methods. Next step consists in classifying the affective state of subjects according to their positivity or negativity (Russell's model, 1980). By means of six independent classifiers, each running a Support Vector Machine algorithm, separate performances are obtained for each class of emotions. The results reveal an interesting “neutral area phenomenon”, where emotions tend to be harder to be detected.Though more frequent, neutral emotions seem to carry less discriminant information than expressive ones. This issue will be a key for designing a tuning step in further research.
Caribbean Academy Of Science
Deshaies, France

hal-01408029
https://hal.univ-antilles.fr/hal-01408029

Éditeur(s) : HAL CCSD North Atlantic Science Publishing Company
Résumé : International audience
By means of the Yosida approximate of an accretive operator, we extended two recent results by Chidume and Chidume and Zegeye (2003) to set-valued operators, and we made the connection with two recent convergence results obtained by Benavides etal for a relaxed version of the so-called proximal point algorithm.
ISSN: 1048-9533

hal-00780243
https://hal.univ-antilles.fr/hal-00780243
https://hal.univ-antilles.fr/hal-00780243/document
https://hal.univ-antilles.fr/hal-00780243/file/056704.pdf
DOI : 10.1155/JAMSA/2006/56704

Éditeur(s) : HAL CCSD springer
Résumé : International audience
In this paper, we address the problem of flood prediction in complex situations. We present an original solution in order to achieve the main goals of accuracy, flexibility and readability. We propose the SM2D modular data driven approach that provides predictive models for each sub-process of a global hydrological process. We show that this solution improves the predictive accuracy regarding a global approach. The originality of our proposition is threefold: (1) the predictive model is defined as a set of aggregate variables that act as classifiers, (2) an evolutionary technique is implemented to find best juries of such classifiers and (3) the flood process complexity problem is addressed by searching for sub-models on sub-processes identified partly by spatial criteria. The solution has proved to perform well on flash flood phenomena of tropical areas known to be hardly predictable. It was indeed successfully applied on a real caribbean river dataset after both preprocessing and preliminary analysis steps presented in the paper.
Lecture notes in computer science
Singapour, Singapore

hal-00878780
https://hal.archives-ouvertes.fr/hal-00878780
DOI : 10.1007/978-3-642-40897-7_13

Éditeur(s) : HAL CCSD Elsevier
Résumé : International audience
A comprehensive inventory of global biodiversity would be greatly improved by automating methods for species delimitation. The Automatic Barcode Gap Discovery method, the Poisson tree processes algorithm and the Generalized mixed Yule coalescent model have been proposed as means of increasing the rate of biodiversity description using single locus data. We applied these methods to explore the diversity within the Aglaopheniidae, a hydrozoan family with many species widely distributed across tropical and tem perate oceans. Our analyses revealed widespread cryptic diversity in this family, almost half of the morpho species presenting several independent evolutionary lineages, as well as support for cases of synonymy. For two common species of this family, Lytocarpia brevirostris and Macrorhynchia phoenicea, we compared the outputs to clustering analyses based on microsatellite data and to nuclear gene phylo genies. For L. brevirostris, microsatellite data were congruent with results of the species delimitation methods, revealing the existence of two cryptic species with Indo Pacific distribution. For M. phoenicea, all analyses confirmed the presence of two cryptic species within the South Western Indian Ocean. Our study suggests that the diversity of Aglaopheniidae might be much higher than assumed, likely related to low dispersal capacities. Sequence based species delimitation methods seem highly valuable to reveal cryptic diversity in hydrozoans; their application in an integrative framework will be very useful in describing the phyletic diversity of these organisms.
ISSN: 1055-7903

hal-01359407
https://hal.archives-ouvertes.fr/hal-01359407
https://hal.archives-ouvertes.fr/hal-01359407/document
https://hal.archives-ouvertes.fr/hal-01359407/file/Postaire-etal2016MolPhylEvol_sp_delim_hydraires_HAL.pdf
DOI : 10.1016/j.ympev.2016.08.013

Éditeur(s) : HAL CCSD
Résumé : International audience
The aim of this study is to perform a simulation of large scale Wireless Sensor Networks (WSN) working on medical diagnosis. The main feature of this WSN is its density and the fact that all sensors are in the same radio range. Our approach helps medical staff to diagnose diseases in an automatic way. In this context, each patient is equipped to a set of sensors. Each sensor is connected to a transducer dedicated to measure a specific health parameter . This WSN will perform some computations and run an alarm when some diseases are suspected. This technique is based on the population protocol to handle data exchanged between sensors. This approach is in fact an efficient distributed algorithm which implies that the diagnose may be done by any sensor dealing with the disease detection. The main result of this paper is: the method supports large scalability which proves its practicability for real cases.
Computers and Communications (ISCC), 2010 IEEE Symposium on Computers and Communications.
Riccione, Italy

hal-00519595
https://hal.archives-ouvertes.fr/hal-00519595

Éditeur(s) : HAL CCSD Springer Verlag
Résumé : International audience
We study the convergence of the Mann Iteration applied to the partial complement of a firmly nonexpansive operator with respect to a linear subspace of a Hilbert space. A new concept considered here. A regularized version is also proposed. Furthermore, to motivate this concept, some applications to robust regression procedures and location problems are proposed.
ISSN: 1862-4472

hal-00776655
https://hal.univ-antilles.fr/hal-00776655
DOI : 10.1007/s11590-009-0172-3

Éditeur(s) : HAL CCSD Springer Verlag
Résumé : International audience
Algorithms issued from the NonLinear Galerkin method have been used in many situations and with different discretizations for the resolution of evolutionary nonlinear equations. The main idea of these methods is to use a splitting of the solution in order to model the equation. According to the splitting of the solution, a splitting of the equation is obtained. The modeling principle is to freeze terms which have a small time variation. In this work we use wavelet discretizations of the 2-D Burgers equations and compare the results with the hierarchical finite elements method. The numerical tests indicate that wavelets give better results than finite elements
ISSN: 0885-7474

hal-00383423
https://hal.archives-ouvertes.fr/hal-00383423
DOI : 10.1007/s10915-004-4806-4

Éditeur(s) : HAL CCSD
Résumé : Session "Posters"
National audience
Nous présentons une méthode permettant la mesure complète de la pose de la tête lors de captures vidéo monoculaires. Ce procédé utilise un modèle de visage et de texture précis. Le modèle facial, construit à partir d'une distribution de scans 3D haute résolution de visages, permet de générer des densités adaptées aux résolutions effectives. L'étape d'initialisation de la position du modèle est cruciale car elle conditionne le suivi ultérieur de la pose. Nous proposons ainsi d'utiliser une métrique composite construite sur des textures extraites de trois bases de données différentes. L'algorithme est alors capable de suivre le visage dans de vastes plages de poses avec une grande précision. Nous proposons des séquences vidéo de test dotées de vérité-terrain de pose précise et indépendante (précision de 0.1 degrés RMS)
Actes de la conférence RFIA 2012
Lyon, France

hal-00656565
https://hal.archives-ouvertes.fr/hal-00656565
https://hal.archives-ouvertes.fr/hal-00656565/document
https://hal.archives-ouvertes.fr/hal-00656565/file/rfia2012_submission_118.pdf

Éditeur(s) : HAL CCSD
Résumé : International audience
This paper focuses on the study of the influence of a newly implemented mechanism on a Pittsburgh-like classifier system. The Adapted Pittsburgh Classifier System is a learning classifier system that uses genetic algorithms to evolve its ruleset. The new mechanism discussed is inspired from Wilson work on the eXtended Classifier System (XCS): it allows the concerned LCS to adapt its rule set when facing a new signal by modifying an existing rule. This mechanism is called covering mechanism due to the fact that the rule is covered up by a new rule which is sensitive to this new signal. Effects of this covering mechanism are first measured on the performances of APCS on well known multi-step environments: maze-type environments (Woods 101 and E2). In addition, further measures presented in this paper indicate that we could possibly rely on the behavior of this covering mechanism to automate the research of a correct cognitive capacity needed by the APCS to solve a given multistep problem.
2008 Eighth International Conference on Hybrid Intelligent Systems
Barcelone, Spain

hal-00520608
https://hal.archives-ouvertes.fr/hal-00520608
DOI : 10.1109/HIS.2008.105

Éditeur(s) : HAL CCSD European Geosciences Union
Résumé : International audience
Natural disturbances are the dominant form of forest regeneration and dynamics in unmanaged tropical forests. Monitoring the size distribution of treefall gaps is important to better understand and predict the carbon budget in response to land use and other global changes. In this study, we model the size frequency distribution of natural canopy gaps with a discrete power law distribution. We use a Bayesian framework to introduce and test, using Monte Carlo Markov chain and Kuo–Mallick algorithms, the effect of local physical environment on gap size distribution. We apply our methodological framework to an original light detecting and ranging dataset in which natural forest gaps were delineated over 30 000 ha of unmanaged forest. We highlight strong links between gap size distribution and environment, primarily hydrological conditions and topography, with large gaps being more frequent on floodplains and in wind-exposed areas. In the future, we plan to apply our methodological framework on a larger scale using satellite data. Additionally , although gap size distribution variation is clearly under environmental control, variation in gap size distribution in time should be tested against climate variability.
ISSN: 1726-4170

hal-01590729
https://hal-univ-guyane.archives-ouvertes.fr/hal-01590729
https://hal-univ-guyane.archives-ouvertes.fr/hal-01590729/document
https://hal-univ-guyane.archives-ouvertes.fr/hal-01590729/file/bg-14-353-2017.pdf
DOI : 10.5194/bg-14-353-2017

Éditeur(s) : HAL CCSD Springer
Résumé : Borehole logs provide in situ information about the fluctuations of petrophysical properties with depth and thus allow the characterization of the crustal heterogeneities. A detailed investigation of these measurements may lead to extract features of the geological media. In this study, we suggest a regularity analysis based on the continuous wavelet transform to examine sonic logs data. The description of the local behavior of the logs at each depth is carried out using the local Hurst exponent estimated by two (02) approaches: the local wavelet approach and the average-local wavelet approach. Firstly, a synthetic log, generated using the random midpoints displacement algorithm, is processed by the regularity analysis. The obtained Hurst curves allowed the discernment of the different layers composing the simulated geological model. Next, this analysis is extended to real sonic logs data recorded at the Kontinentales Tiefbohrprogramm (KTB) pilot borehole (Continental Deep Drilling Program, Germany). The results show a significant correlation between the estimated Hurst exponents and the lithological discontinuities crossed by the well. Hence, the Hurst exponent can be used as a tool to characterize underground heterogeneities.
ISSN: 1866-7411

hal-00617470
https://hal.archives-ouvertes.fr/hal-00617470
DOI : 10.1007/s12517-010-0129-y

Éditeur(s) : HAL CCSD
Résumé : International audience
The aim of this study is to suggest an automated technique for distributed decision. It is based on protocol population deployed on Wireless Sensor Networks (WSN). This approach is able to help medical staff to detect earlier than usual some diseases on patients. It could be easily adapted for many other fields (fire monitoring, environment supervising, ...) In this context, a patient is equipped with health parameter transducers which are connected to a WSN. This WSN will perform some computations and raise an alarm when some diseases are suspected. The algorithm is distributed, i.e., the decision may be done by any mote dealing with the disease detection. The experimentations show promising results.
a venir
Denver, Colorado, United States

hal-00519597
https://hal.archives-ouvertes.fr/hal-00519597

Éditeur(s) : HAL CCSD IEEE
Résumé : International audience
This paper proposes a novel automated approach for the categorization of cells in fluorescence microscopy images. Our supervised classification method aims at recognizing patterns of unlabeled cells based on an annotated dataset. First, the cell images need to be indexed by encoding them in a feature space. For this purpose, we propose tailored bio-inspired features relying on the distribution of contrast information. Then, a supervised learning algorithm is proposed for classifying the cells. We carried out experiments on cellular images related to the diagnosis of autoimmune diseases, testing our classification method on the HEp-2 Cells dataset of Foggia et al (CBMS 2010). Results show classification precision larger than 96% on average, thus confirming promising application of our approach to the challenging application of cellular image classification for computer-aided diagnosis.
ICPR 2012
Tsukuba, Japan

hal-00958856
https://hal.archives-ouvertes.fr/hal-00958856
https://hal.archives-ouvertes.fr/hal-00958856/document
https://hal.archives-ouvertes.fr/hal-00958856/file/icpr_2012.pdf

Éditeur(s) : HAL CCSD
Résumé : LPSC14037
Scientific data collected with modern sensors or dedicated detectors exceed very often the perimeter of the initial scientific design. These data are obtained more and more frequently with large material and human efforts. A large class of scientific experiments are in fact unique because of their large scale, with very small chances to be repeated and to superseded by new experiments in the same domain: for instance high energy physics and astrophysics experiments involve multi-annual developments and a simple duplication of efforts in order to reproduce old data is simply not affordable. Other scientific experiments are in fact unique by nature: earth science, medical sciences etc. since the collected data is "time-stamped" and thereby non-reproducible by new experiments or observations. In addition, scientific data collection increased dramatically in the recent years, participating to the so-called "data deluge" and inviting for common reflection in the context of "big data" investigations. The new knowledge obtained using these data should be preserved long term such that the access and the re-use are made possible and lead to an enhancement of the initial investment. Data observatories, based on open access policies and coupled with multi-disciplinary techniques for indexing and mining may lead to truly new paradigms in science. It is therefore of outmost importance to pursue a coherent and vigorous approach to preserve the scientific data at long term. The preservation remains nevertheless a challenge due to the complexity of the data structure, the fragility of the custom-made software environments as well as the lack of rigorous approaches in workflows and algorithms. To address this challenge, the PREDON project has been initiated in France in 2012 within the MASTODONS program: a Big Data scientific challenge, initiated and supported by the Interdisciplinary Mission of the National Centre for Scientific Research (CNRS). PREDON is a study group formed by researchers from different disciplines and institutes. Several meetings and workshops lead to a rich exchange in ideas, paradigms and methods. The present document includes contributions of the participants to the PREDON Study Group, as well as invited papers, related to the scientific case, methodology and technology. This document should be read as a "facts finding" resource pointing to a concrete and significant scientific interest for long term research data preservation, as well as to cutting edge methods and technologies to achieve this goal. A sustained, coherent and long term action in the area of scientific data preservation would be highly beneficial.
http://hal.in2p3.fr/in2p3-00959072

in2p3-00959072
http://hal.in2p3.fr/in2p3-00959072
http://hal.in2p3.fr/in2p3-00959072/document
http://hal.in2p3.fr/in2p3-00959072/file/PREDON_Scientific_Data_Preservation_2014.pdf

Éditeur(s) : HAL CCSD Elsevier
Résumé : International audience
STUDY OBJECTIVE: There is no consensus about the management of large spontaneous pneumothoraces. Guidelines recommend either needle aspiration or chest tube drainage and most patients are hospitalized. We assess the efficiency of ambulatory management of large spontaneous pneumothoraces with pigtail catheters. METHODS: From February 2007 to January 2011, all primary and secondary large spontaneous pneumothoraces from Lorient's hospital (France) were managed with pigtail catheters with a 1-way valve. The patients were discharged immediately and then evaluated every 2 days according to a specific algorithm. RESULTS: Of the 132 consecutive patients (110 primary, 22 secondary), 103 were exclusively managed as outpatients, with full resolution of the pneumothorax by day 2 or 4, which represents an ambulatory success rate of 78%. Mean time (SD) of drainage was 3.4 days (1.8). Seven patients were initially hospitalized but quickly discharged and had full resolution by day 2 or 4, leading to a total success rate of 83%. The use of analgesics was low. The 1-year recurrence rate was 26%. If successful, this outpatient management is potentially cost saving, with a mean cost of 926, assuming up to 2 outpatient visits and 1 chest radiograph, compared with 4,276 if a chest tube was placed and the patient was admitted to the hospital for 4 days. CONCLUSION: Ambulatory management with pigtail catheters with 1-way valves could be a reasonable first-line of treatment for large spontaneous pneumothoraces. Compared with that of other studies, our protocol does not require hospitalization and is cost saving.
ISSN: 0196-0644

hal-01063942
https://hal.archives-ouvertes.fr/hal-01063942
DOI : 10.1016/j.annemergmed.2013.12.017
PUBMED : 24439715

Éditeur(s) : HAL CCSD
Résumé : International audience
We propose using a distributed algorithm to count individuals in a population by way of a 3-phase algorithm. The first phase consists of detecting the presence of individuals, the second allows counting the number of individuals and the last aggregates the numbers of individuals over several paths. We propose an approach that uses a wireless sensor network built on a linear architecture. Here, each mote has a successor and a predecessor.
Wireless Communications in Unusual and Confined Areas (ICWCUCA), 2012 International Conference on

hal-00857695
https://hal.archives-ouvertes.fr/hal-00857695
DOI : 10.1109/ICWCUCA.2012.6402496

Éditeur(s) : HAL CCSD Cépaduès-Éditions
Résumé : International audience
Nous présentons dans cet article un nouvel automate : le FIA qui permet de traiter de façon efficace la problématique de l'extraction des itemsets fréquents dans les data streams. Le FIA est une structure de données très compacte et informative qui, par ailleurs, présente des propriétés incrémentales facilitant grandement la mise à jour avec une granularité très fine. L'algorithme développé pour la mise à jour du FIA effectue un unique passage sur les données qui sont prises en compte par batch, itemset par itemset et pour chaque itemset, item par item. Utilisé dans le cadre d'une approche prédictive, le FIA permet d'indexer les itemsets véritablement fréquents du stream en maximisant soit le rappel soit la précision.
EGC: Extraction et Gestion des Connaissances
Nice, France

hal-00447420
https://hal.archives-ouvertes.fr/hal-00447420
https://hal.archives-ouvertes.fr/hal-00447420/document
https://hal.archives-ouvertes.fr/hal-00447420/file/2008--Jean-Emile_Symphor--Le_FIA_un_nouvel_automate_permettant_l_extraction_efficace_d_itemsets_frequents_dans_les_data_streams.pdf