Éditeur(s) : Gauthier-Villars
Résumé : Calcareous nannofossil assemblages of the family Noelaerhabdaceae have been studied in sediments of seventeen Quaternary cores raised from various climatic areas of the Atlantic and Pacific oceans. These sections display a regular, hiatus-free sedimentation for the last 500000 years. They have been dated using oxygen-isotopic measurements, variations of calcium carbonate content, variations of total nannofossil abundance, thorium measurements and volcanic ash horizons. Coccoliths of the genus Gephyrocapsa have been placed in three distinct taxonomic groups, based on morphological criteria inferred from light-microscope observations. Their acmes, as well as the acme of Emiliania huxleyi, are considered as stratigraphic markers. These markers characterize most of the last thirteen glacial-interglacial climatic stages, as well as some climatic events of lower magnitude (8.5 and 6.5). Most of these markers have global stratigraphic significance: acme of ''closed'' Gephyrocapsa during stages 13,11 and 9, and during event 8.5; acme of ''small'' Gephyrocapsa during stage 7 and event 6.5; acme of ''open'' Gephyrocapsa at top of event 6.5, and during stages 5 and 3; acme of E. huxleyi during stages 3 and 1. Others are only valid south of the southernmost latitude reached by the North-Atlantic polar front during the Quaternary: acme of ''closed'' Gephyrocapsa during stage 12; acme of ''small'' Gepkyrocapsa in early and middle stage 5; acme of E. huxleyi during stage 2. Others are only valid south of 20-degrees-S: acme of ''small'' Gephyrocapsa at the 10/9 stage boundary; acme of ''open'' Gephyrocapsa during stage 6.
Oceanologica Acta (0399-1784) (Gauthier-Villars), 1993 , Vol. 16 , N. 4 , P. 349-362

Droits : info:eu-repo/semantics/openAccess
http://archimer.ifremer.fr/doc/00099/21061/18687.pdf
http://archimer.ifremer.fr/doc/00099/21061/

Éditeur(s) : HAL CCSD
Résumé : International audience
In this article, we analyse a collaborative network to understand the underlying patterns that structure the co-writing process of scientific articles. Our goal is to identify and understand the collaboration tendencies from authors publishing activities. For this purpose, we adopt a descriptive modelling through a network approach that consists first in generating the collaborative network from data on publications. Nodes of the network are then enriched with a set of individual attributes extracted from the publishing activity of each author. Finally, we search for conceptual views, a recent link clustering approach, which allows to summarize any kind of networks by highlighting the sets of attributes found frequently linked. Results show that it exists strong tendencies that unconsciously structure the collaboration behaviours. In this paper, we present these tendencies and show how they evolve according to different extraction thresholds.
EEE/ACM International Conference on Advances in Social Networks Analysis and Mining
Sydney, Australia

hal-01637563
https://hal.archives-ouvertes.fr/hal-01637563
DOI : 10.1145/3110025.3110146

Éditeur(s) : HAL CCSD ACM
Résumé : International audience
Applications over wireless sensor networks are growing quickly. Traditional software development tools are not well adapted to this technology. In particular, adequate testing methodologies are required. Many issues have not been formally addressed as energy-conservation, congestion control, reliability data dissemination, security. In this paper, we present a pragmatic approach to detect some kind of anomalies based on defined scenarios on wireless sensor networks. A scenario is considered as a set of events which should happen on the network in an ordered way. We discuss a formal architecture able to perform these scenarios over the wireless sensor networks and to raise alarms if necessary. This methodology has been implemented on a prototype and has been experimented with various examples. This contribution is a first attempt for a formal testing methodology for wireless sensor networks.
Proceedings of the 6th ACM workshop on QoS and security for wireless and mobile networks

Droits : info:eu-repo/semantics/OpenAccess
hal-00596118
https://hal.archives-ouvertes.fr/hal-00596118
https://hal.archives-ouvertes.fr/hal-00596118/document
https://hal.archives-ouvertes.fr/hal-00596118/file/Q2sWinet_10.pdf
DOI : 10.1145/1868630.1868641

Éditeur(s) : HAL CCSD
Résumé : International audience
Human spatial motions determine geographic social contacts that influence the way an information is spread on a population or a community. As mobility is a transverse dimension to social practices it is important to better understand its role. With the Eternal-Return model we propose, we simulate an artificial world populated by heterogeneous agents who differ in their mobility. We have chosen a multi-agent framework perspective for this simulation. We endow the agents with simple rules on how to move around the space and how to establish proximity-contacts. This allows to distinguish different kinds of mobile agents, from sedentary ones to travelers. To summarize the dynamics induced by mobility over time, we define the mobility-based Social Proximity Network as being the network of all distinct contacts between agents. Its properties give insight in the process of information spreading. We conduct simulations to understand how an information can be broadcast when agent-nodes are in motion.
IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
Niagara falls, Canada

hal-00874344
https://hal.archives-ouvertes.fr/hal-00874344

Éditeur(s) : HAL CCSD ACM
Résumé : International audience
In this study, we use an adapted version of Pitsburgh-like learning classifier system to perform over classification tasks. The Adapted Pittsburgh Classifier System, enhanced with a new mechanism, allows us to consider the classification problems and their treatment by a given LCS in a different manner. Our aim is to exhibit elements in order to prove that, using the action covering mechanism, this system is able to build an inner map of a given classification learning sample. In the context of this paper, this map is built using an intrisic property of Pittsburgh-like CS: the use of various collections of classifiers amongst a unique population.
Proceedings of the 12th annual conference comp on Genetic and evolutionary computation
Portland,Oregon, United States

hal-00520609
https://hal.archives-ouvertes.fr/hal-00520609
DOI : 10.1145/1830761.1830823

Éditeur(s) : HAL CCSD INRIA
Résumé : National audience
Non seulement les organismes financiers se disputent les meilleurs mathématiciens mais la finance est devenue source de problèmes théoriques inédits en mathématiques.
Les Cahiers de l'INRIA - La Recherche

Droits : info:eu-repo/semantics/OpenAccess
inria-00527579
https://hal.inria.fr/inria-00527579
https://hal.inria.fr/inria-00527579/document
https://hal.inria.fr/inria-00527579/file/inria-n429-avr09.pdf

Éditeur(s) : HAL CCSD ACM
Résumé : International audience
In 2008 a scientific paper written by Butz and al. investigated Matching in Learning Classifier Systems. Matching represents at least 65% of the computational time when executing a classifier system as reported in Llora and al. We propose to modify that encoding using a fast and accurate matching replacing standard matching algorithm for character-based classifier systems.
Proceedings of the 12th annual conference comp on Genetic and evolutionary computation
Portland, Oregon, United States

hal-00520610
https://hal.archives-ouvertes.fr/hal-00520610
DOI : 10.1145/1830761.1830820

Extrait de : L'illustration, n°277, p. 119-121
Résumé : Article et photographies 4 p.
Siècle(s) traité(s) : 20
Droits : Domaine public
Provenance : ORkidé|Fonds privé Pierre Rostan
Permalien : http://www.manioc.org/patrimon/ORK12155
ORK12155

Éditeur(s) : HAL CCSD
Résumé : International audience
In this work, we propose a novel approach for the discovery of frequent patterns in a social network on the basis of both vertex attributes and link frequency. With an analogy to the traditional task of mining frequent item sets, we show that the issue addressed can be formulated in terms of a conceptual analysis that elicits conceptual links. A social-based conceptual link is a synthetic representation of a set of links between groups of vertexes that share similar internal properties. We propose a first algorithm that optimizes the search into the concept lattice of conceptual links and extracts maximal frequent conceptual links. We study the performances of our solution and give experimental results obtained on a sample example. Finally we show that the set of conceptual links extracted provides a conceptual view of the social network.
IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)
Istanbul, Turkey

hal-00786161
https://hal.archives-ouvertes.fr/hal-00786161
DOI : 10.1109/ASONAM.2012.15

Éditeur(s) : HAL CCSD ACM New York, NY, USA
Résumé : International audience
This paper focuses on the study of the behavior of a genetic algorithm based classifier system, the Adapted Pittsburgh Classifier System (A.P.C.S), on maze type environments containing aliasing squares. This type of environment is often used in reinforcement learning litterature to assess the performances of learning methods when facing problems containing non markov situations. Through this study, we discuss on the performances of the APCS on maze type environments and also of the efficiency of an improvement of the APCS learning method inspired from the XCS : the covering mechanism. We manage to show that, without any memory mechanism, the APCS is able to build and to keep accurate strategies to produce regular sub-optimal solutions to these maze problem. This statement is shown through a comparison of the results obtained by the XCS, XCSM and XCSMH on distinct maze problems with these obtained by the APCS.
Proceedings of the 2008 GECCO conference companion on Genetic and evolutionary computation
Atlanta, GA, United States

hal-00520607
https://hal.archives-ouvertes.fr/hal-00520607
DOI : 10.1145/1388969.1389013

Éditeur(s) : HAL CCSD ACM
Résumé : International audience
This study presents two algorithms that count birds with wireless sensors equipped with microphones. Audio inputs are parametrized to get some kind of fingerprints which are used to recognize the song of the birds in a classification process. Afterward, counting algorithms derive an estimate of the number of singing birds in the habitat. Unlike traditional approaches which leverage the audio waveform to get the location of the targets, we use a trilateration technique on graphs derived from the detection of the birds. These graphs exhibit nice properties which enable the finding of the estimate in polynomial time. Further, experiments are conducted and confirmm the efficiency of our counting algorithms even in the presence of noise.
Proceedings of the 6th ACM symposium on Performance evaluation of wireless ad hoc, sensor, and ubiquitous networks
New York, United States

hal-00602263
https://hal.archives-ouvertes.fr/hal-00602263
DOI : 10.1145/1641876.1641891

Éditeur(s) : HAL CCSD ACM
Résumé : International audience
Environmental resources (e.g., air quality, water quantity) are needed to understand fundamental questions such as global change. Such resources are often collected from sensors, including humans acting as sensors. Tools have emerged to manage such data in the form of time series and, in particular, the Sensor Observation Service (SOS) which offers a framework based on predefined relational database schema. Environmental observatories can be built using such frameworks, allowing to address specific key scientific questions by collecting and sharing large-scale environmental data. However, the strict schema of SOS database makes it difficult to integrate some data that cannot be directly mapped to the schema. Guidelines and best practices are offered in the literature in order to reuse standards from the Semantic Web but they do not cover all needs. In particular, they do not help to reflect the fact that a single environmental database can lead to several SOS models. Since being aware of these multiple possibilities is crucial for a better use of the observatories, we argue that some extensions of the existing works are required. In this paper, we thus propose an extension of existing vocabularies to achieve this goal. Our contribution is illustrated on the real case of the Lebanese-French O-LiFE environmental observatory.
6th ACM International Conference on Web Intelligence, Mining and Semantics
Nimes, France

lirmm-01381082
https://hal-lirmm.ccsd.cnrs.fr/lirmm-01381082
https://hal-lirmm.ccsd.cnrs.fr/lirmm-01381082/document
https://hal-lirmm.ccsd.cnrs.fr/lirmm-01381082/file/presentationwims_s1_2.pdf
DOI : 10.1145/2912845.2912856

Éditeur(s) : London : John Murray
Siècle(s) traité(s) : 19
Droits : Domaine public
Provenance : Ville de Pointe-à-Pitre. Réseau des bibliothèques
Permalien : http://www.manioc.org/patrimon/PAP11051
PAP11051

Éditeur(s) : HAL CCSD
Résumé : International audience
Numerous social network mining methods have been proposed until now for addressing social mining tasks and specially searching for communities or frequent social patterns. However, the degree of complementarity of these methods has been very little studied. In this paper, we focus on two knowledge extraction processes in social networks: a link-based clustering that may extract social communities and a recent approach that searches for frequent conceptual link involving both clustering and search for frequent social patterns. We explore how the models extracted by each method may match and which potential useful knowledge they may provide. Our objective is to evaluate the potential relationships between communities and frequent conceptual links. For this purpose, we propose a set of measures for evaluating the degree to which these patterns extracted from the same dataset are matching. Our approach is applied on two datasets and demonstrates the importance of considering simultaneously various kinds of knowledge and their complementarity.
IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
Niagara falls, Canada

hal-00874351
https://hal.archives-ouvertes.fr/hal-00874351

Éditeur(s) : HAL CCSD Springer Verlag
Résumé : 17 pages, 11 figures.
International audience
The problem addressed in this paper is the automatic extraction of names from a document image. Our approach relies on the combination of two complementary analyses. First, the image-based analysis exploits visual clues to select the regions of interest in the document. Second, the textual-based analysis searches for name patterns and low-level word textual features. Both analyses are then combined at the word level through a neural network fusion scheme. Reported results on degraded documents such as facsimile and photocopied technical journals demonstrate the interest of the combined approach.
ISSN: 1433-7541

hal-00329459
https://hal.archives-ouvertes.fr/hal-00329459
DOI : 10.1007/s10044-006-0038-6

Éditeur(s) : HAL CCSD
Résumé : International audience
In this work, we focus on the issue of diffusion in dynamic networks. We begin by proposing a generic framework that merges two essential aspects of the problem: diffusion and network dynamics. Then, our framework is used for comparing effects of two aspects of the human behavior, sociability and network dynamics. On the one hand the dynamics of the network is related to the movements of individuals in a social space that lead ephemeral social proximity contacts. On the other hand the diffusion phenomenon is studied through the epidemic paradigm. The results obtained by simulations provide original insight about how and why the "social dynamics" of individuals, related to the proximity in a social space and its evolutions, influences diffusion phenomena through a population.
International Conference on Advances in Social Networks Analysis and Mining
Istanbul, Turkey

hal-00786162
https://hal.archives-ouvertes.fr/hal-00786162
DOI : 10.1109/ASONAM.2012.104

Éditeur(s) : Paris : Hachette
Siècle(s) traité(s) : 19
Droits : Domaine public
Provenance : Collectivité territoriale de Guyane. Bibliothèque Alexandre-Franconie
Permalien : http://www.manioc.org/patrimon/FRA12068
FRA12068

Éditeur(s) : HAL CCSD
Résumé : International audience
In this paper, we focus on the very specificity of rumors as pieces of information for modeling their process of propagation. We consider a population of pedestrians walking in a city and we assume that a rumor is transmitted by word of mouth from one to another. Although the diffusion of a rumor is of course a multi-dimensional process driven by sociological, economical and psychological elements, in this first step, we emphasize one main dimension of this complex phenomenon only. This dimension is the neighborhood of individuals likely to spread the information. With a confrontation of two antagonistic properties of the neighborhood that are profusion and scarcity of spreaders, we highlight specific characteristics of rumors. This study could lead to the psychological mechanism involved in the decision for a person to become or not a spreader himself/herself. In summary, we study if scarcity could be the silver bullet explaining how a rumor spreads.
ASONAM 2015 : IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
Paris, France

hal-01252936
https://hal.archives-ouvertes.fr/hal-01252936
DOI : 10.1145/2808797.2809299

Éditeur(s) : HAL CCSD Presses Universitaires de Louvain (distribution I6DOC/CIACO)
Résumé : In French. 10 pages, 5 figures, LaTeX 2e using EPSF and custom package taln2006.sty (designed by Pierre Zweigenbaum, ATALA). Proceedings of the 13th annual French-speaking conference on Natural Language Processing: `Traitement Automatique des Langues Naturelles' (TALN 2006), Louvain (Leuven), Belgium, 10-13 April 2003
National audience
We propose a theoretical framework within which information on the vocabulary of a given corpus can be inferred on the basis of statistical information gathered on that corpus. Inferences can be made on the categories of the words in the vocabulary, and on their syntactical properties within particular languages. Based on the same statistical data, it is possible to build matrices of syntagmatic similarity (bigram transition matrices) or paradigmatic similarity (probability for any pair of words to share common contexts). When clustered with respect to their syntagmatic similarity, words tend to group into sublanguage vocabularies, and when clustered with respect to their paradigmatic similarity, into syntactic or semantic classes. Experiments have explored the first of these two possibilities. Their results are interpreted in the frame of a Markov chain modelling of the corpus' generative processe(s): we show that the results of a spectral analysis of the transition matrix can be interpreted as probability distributions of words within clusters. This method yields a soft clustering of the vocabulary into sublanguages which contribute to the generation of heterogeneous corpora. As an application, we show how multilingual texts can be visually segmented into linguistically homogeneous segments. Our method is specifically useful in the case of related languages which happened to be mixed in corpora.
Verbum ex machina : Actes de la 13ème conférence annuelle sur le Traitement Automatique des Langues Naturelles
Louvain (Leuven), Belgium

hal-00327607
https://hal.archives-ouvertes.fr/hal-00327607
ARXIV : 0810.1212

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