Éditeur(s) : HAL CCSD
Résumé : International audience
The increasing development of world trade has promoted the spread of diseases. Recent events, like the H1N1 outbreak and spread, have confirmed this tendency. Everyone could observe that this kind of infectious disease often has the ability to cross countries borders and spread rapidly. Preventing, monitoring and controlling the outbreak of these diseases have appeared to be a public health problem of primary importance for years. However, although numerous works have been conducted in order to understand and study epidemics, this subject remains a topical issue because of the complexity of the phenomena. In this paper, we present new opportunities offered by the field of social networks for understanding the spread of infectious diseases. This work focuses both on techniques already used in epidemiology, and very recent works in social network analysis that open new perspectives. We give an overview of methods currently used to model and study the spread of diseases and future directions that the social network approach allows to glimpse.
2011 Fifth International Conference on Research Challenges in Information Science (RCIS)
Gosier, Guadeloupe

hal-00624364
https://hal.archives-ouvertes.fr/hal-00624364
DOI : 10.1109/RCIS.2011.6006866

Éditeur(s) : HAL CCSD
Résumé : International audience
We instrumented a car simulator by gathering low level data and fed it to an artificial neural network in order to perform blood alcohol content (BAC) estimations. The results depend on the quality of the data extraction and processing, and also on the selected inputs. We explain our data extraction and processing methodology, and how we used it to generate reliable and comparable features. At last, we describe the performances of individual features and how they combine. In the end, the prototype was able to accurately estimate the BAC value of a subject after being trained with driving samples of this subject with various BAC values.
Proceedings of ACHI 2013, The Sixth International Conference on Advances in Computer-Human Interactions
Nice, France

hal-00850137
https://hal.archives-ouvertes.fr/hal-00850137

Éditeur(s) : HAL CCSD Elsevier
Résumé : International audience
ISSN: 0378-3839

hal-00385746
https://hal.archives-ouvertes.fr/hal-00385746

Éditeur(s) : HAL CCSD
Résumé : International audience
This paper introduces the information criteria in feature selection framework. Information criteria are integrated in feature selection scheme to select subset candidates. The accuracy of the proposed approach is based on the quality of the probability density approximations of these features. They are obtained using histograms optimized thanks to the adaptive arithmetic coding principles. Tests on simulated data and references are made. Multiple classifiers are used. The correct classification rate shows, the importance of this tools and its ability to select a best subsets. Generally, the subsets produce a good characterization of classes which the data belong.
TAIMA Proceedings

hal-00634754
https://hal.archives-ouvertes.fr/hal-00634754

Éditeur(s) : HAL CCSD Springer Verlag
Résumé : International audience
Random walk (RW) or Continuous Time Random Walk (CTRW) are recurring Monte Carlo methods used to model convective and diffusive transport in complex heterogeneous media. Many applications can be found, including fluid mechanic, hydrology, and chemical reactors modeling. These methods are easy to implement, very versatile and flexible enough to become appealing for many applications because they generally overlook of deeply simplify the building of explicit complex meshes required by deterministic methods. RW and CTRW provide a good physical understanding of the interactions between the space scales of het-erogeneities and the transport phenomena under consideration. In addition, they can result in efficient up-scaling methods, especially in context of flow and transport in fractured media. In the present study, we review the applications of RW or CTRW for several situations coping with various spatial scales, and different insights into up-scaling applications. RW and CTRW advantages and downsides are also discussed, thus providing a few avenues for further works and applications.
ISSN: 0169-3913

hal-01449131
https://hal.archives-ouvertes.fr/hal-01449131
https://hal.archives-ouvertes.fr/hal-01449131/document
https://hal.archives-ouvertes.fr/hal-01449131/file/0025972-02.pdf
DOI : 10.1007/s11242-016-0693-z

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
Résumé : International audience
This paper proposes a new knowledge discovery method called FLMin to discover frequent patterns in a social network. The algorithm works without previous knowledge on the network and exploits both the structure and the attributes of nodes to extract regularities called Frequent Links. Unlike traditional works in this area that solely exploit structural regularities of the network, the originality of FLMin is its ability to gather these two kinds of information in the search for patterns. In this paper, we detail the method proposed for extracting frequent links and discuss its complexity and its flexibility. The efficiency of our solution is evaluated by conducting qualitative and quantitative studies for understanding how behaves FLMin according to different parameters.
Networked Digital Technologies
Dubai, United Arab Emirates

hal-00768431
https://hal.archives-ouvertes.fr/hal-00768431
DOI : 10.1007/978-3-642-30567-2_38

Éditeur(s) : HAL CCSD
Résumé : International audience
The paper proposes a new knowledge discovery method called MAX-FLMin for extracting frequent patterns in social networks. Unlike traditional approaches that mainly focus on the network topological structure, the originality of our solution is its ability to exploit information both on the network structure and the attributes of nodes in order to elicit specific regularities that we call "Frequent Links". This kind of patterns provides relevant knowledge about the groups of nodes most connected within the network. First, we detail the method proposed to extract maximal frequent links from social networks. Second, we show how the extracted patterns are used to generate aggregated networks that represent the initial social network with more semantics. Qualitative and quantitative studies are conducted to evaluate the performances of our algorithm in various configurations.
Database (Weston, Conn.) and Expert Systems Applications
Vienna, Austria

hal-00767052
https://hal.archives-ouvertes.fr/hal-00767052
DOI : 10.1007/978-3-642-32600-4_35

Éditeur(s) : HAL CCSD
Résumé : National audience
Traditional network generation models attempt to replicate global structural properties (degree distribution, average distance, clustering coefficient, communities, etc.) through synthetic link formation mechanisms such as triadic closure or preferential attachment. In this work, we study the evolution of a very big communication network coming from mobile telephony and we analyse the link formation process. A first study conducted on the standard mechanisms allows observing that several mechanisms are responsible for the properties observed in this network. In a second study, we characterize more precisely the link formation process by searching for correlations between the probability of creating a new link and some individual properties such as the degree, the clustering coefficient and the age of the nodes.
Conférence sur les modèles et l'analyse des réseaux : Approches mathématiques et informatiques
Saint-Etienne, France

hal-00873990
https://hal.archives-ouvertes.fr/hal-00873990

Éditeur(s) : HAL CCSD
Résumé : International audience
Optimizing the resource extraction and limiting the environmental constraint motivate to accurately characterize reservoirs. The extraction of resources induces volume change of the reservoir causing displacements in the surrounding medium up to the surface. The resulting surface deformation is usually significant enough to be measurable by geodetic instruments (GPS, satellites, tiltmeters, strainmeters). However, the data needs to be associated to a reservoir model using an inverse scheme to allow the estimation of physical properties of the reservoir. Complete geodetic data including InSAR, GPS, tilt, strain and gravimetric data are uncommon for conventional, unconventional or mining exploitations. In this study, we work on the one site that gathers a wide range of geodetic data: the salt exploitation of Vauvert, France, operated by KemOne. Our approach aims at estimating the volume changes of the cavities created by the extraction combining all the available geodetic data. To do so, we minimize a global functional including weighting factors for each data type. The weighting factors are optimally estimated for our study and can be adapted depending on the issue. Hence, an optimal distribution of data can be suggested for a specific reservoir characterization.
79th EAGE Conference
Paris, France

Droits : http://hal.archives-ouvertes.fr/licences/copyright/
hal-01575426
https://hal.archives-ouvertes.fr/hal-01575426
https://hal.archives-ouvertes.fr/hal-01575426/document
https://hal.archives-ouvertes.fr/hal-01575426/file/reservoir-characterization-inversion.pdf
DOI : 10.3997/2214-4609.201700987

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
Résumé : International audience
In this paper, we focus on providing new tools to help doctors in their diagnosis. We study the feasibility of using a distributed approach over Wireless Sensor Networks (WSN). We define a Wireless Body Area Network (WBAN) as a set of wireless sensors which equipped a patient. Each sensor senses a health parameter, for example, temperature or heart pulse. Our aim is to understand how a distributed approach can be a fair alternative to the common centralized paradigm. We study a distributed approach based on the token paradigm. Then, we compare this approach to the centralized one, throw simulations and experimentations over real sensors.
11th International Conference on Innovative Internet Community Systems

hal-00602207
https://hal.archives-ouvertes.fr/hal-00602207

Éditeur(s) : HAL CCSD
Résumé : International audience
In the network modeling area, the most widely used definition of a "pattern" is that of a subgraph, a notion that considers only the network topological structure. While this definition has been very useful for extracting subgraphs frequently found in a network or a set of networks, it does not take into account the node attributes, an intrinsic component of social networks that often provides relevant information on the role or the position of a node in a network. In this paper, we propose a novel approach for extracting frequent patterns in social networks, called frequent link mining, based on the search for particular patterns that combine information on both network structure and node attributes. This kind of patterns, that we call frequent links, provides knowledge on the groups of nodes connected in the social network. In this article, we detail the method proposed for extracting frequent links and discuss its flexibility and its complexity. We demonstrate the efficiency of our solution by carrying out qualitative and quantitative studies.
Advances in Database (Weston, Conn.)s and Information Systems
Poznań, Poland

hal-00767050
https://hal.archives-ouvertes.fr/hal-00767050
DOI : 10.1007/978-3-642-33074-2_28

Éditeur(s) : HAL CCSD
Résumé : International audience
While the impact of network properties on information spread- ing is now widely studied, in uence of network dynamics is very little known. In this paper, we study how evolution mechanisms tradition- ally observed within social networks can a ect information di usion. We present an approach that merges two models: model of informa- tion di usion through social networks and model of network evolution. Since epidemics provide a reference in application domains of information spreading, we measure the impact of basic network structure changes on epidemic peak value and timing. Then we investigate observed trends in terms of changes appearing in the network structure. Our results provide promising results on how and why network dynamics is a strong param- eter to integrate in requirements for information spreading modelling.
World Summit on the Knowledge Society
Mykonos, Greece

hal-00768405
https://hal.archives-ouvertes.fr/hal-00768405

Éditeur(s) : HAL CCSD
Résumé : International audience
This paper focuses on the study of the behaviour of a singular classifier system, the Adapted Pittsburgh Classifier System (A.P.C.S), on environments containing aliasing situations. Maze type environments are often used in reinforcement learning literature to assess the performances of learning methods when facing problems containing non Markovian situations. Those situations are often encountered when performing reinforcement learning on aliased data samples issued from meteorological simulations.
International Journal of Artificial Intelligence

hal-00520611
https://hal.archives-ouvertes.fr/hal-00520611

Éditeur(s) : HAL CCSD Elsevier
Résumé : International audience
We use 3-D mechanical modeling representing faults as planar surfaces with frictional properties that obey Coulomb-failure process to explore the long-term slip rates of the Altyn Tagh fault and Kunlun faults in the north Tibetan plateau. Crustal theology is simplified as an elastoplastic upper crust and a viscoelastic lower crust. Far-field GPS velocities and late Quaternary fault slip rates are used to constrain the model results. Rheological tests show that effective fault friction lower than 0.1-0.08 leads to high slip rates that fit with geologically and geodetically determined slip rates of the Kunlun fault (10-11.7 +/- 1.5 mm/yr). Meanwhile, the modeled Altyn Tagh fault reaches slip rates similar to 13.7 mm/yr to similar to 7.8 mm/yr in its central portion, between ranges of the geological slip rates. Associated with high slip rates, our model predicts that central Tibet (similar to 84 degrees E-95 degrees E) from the Altyn Tagh fault to the north of the Himalayan arc accommodates north-south shortening and east-west extension rates of similar to 10-12 mm/yr and similar to 8-10 mm/yr, respectively. We also question the widely accepted idea that interseismic strain is driven at the base of the seismogenic zone by a screw dislocation. If this assumption fails, the presented model implies that interseismic strain around large strike-slip faults could be distributed in a much broader way if the lithosphere deforms as a thin elastic plate rather than an elastic half-space with an embedded dislocation. If this distributed deformation is ignored, and the instantaneous surface deformation field modeled as that resulting from slip on a dislocation below a specified depth embedded in an elastic half-space, the estimated slip rate will inevitably be lower than the true long-term slip rate. This appears to explain why geodetic slip rates proposed for the Altyn Tagh fault (510 mm/yr) are lower than some of the geological slip rates. (C) 2008 Elsevier B.V. All rights reserved.
ISSN: 0012-821X

hal-00411926
https://hal.archives-ouvertes.fr/hal-00411926
DOI : 10.1016/j.epsl.2008.06.049

Éditeur(s) : HAL CCSD Springer
Résumé : International audience
Traditional network generation models aim to replicate global structural properties observed on various real-world networks through synthetic link formation mechanisms such as triadic closure or preferential attachment. Nowadays, the large amount of data available allow to study more precisely the link formation processes and to compare models with real situations. In this work, we analyze the network formed by the communication activities of the users of a telephony operator for studying the link formation process. Our goal is to identify the underlying formation mechanisms and checking if they match those proposed in traditional models. Indeed, the communications emitted and received by users are strong indicators for understanding the underlying patterns of the link formation process and highlighting how some individual properties induce the formation process in such a network. In a first study conducted at a global level, we show that the traditional mechanisms commonly used in network generation models cannot reproduce alone the link formation in this network. In a second study, we adopt a new point of view and analyze locally the link formation process by searching for correlations between some user attributes and the formation of the new links. The results obtained show that a very strong percentage of new links are formed between individuals with strong similarity.
ISSN: 1869-5450

hal-01312310
https://hal.univ-antilles.fr/hal-01312310
DOI : 10.1007/s13278-015-0304-y

Éditeur(s) : HAL CCSD
Résumé : International audience
Dans ce papier, nous proposons une solution qui exploite à la fois des informations sur la structure du réseau et sur les attributs des noeuds, pour extraire un nouveau type de motifs que nous appelons "liens conceptuels". Les liens conceptuels sont des représentations synthétiques d'ensembles de liens entre des groupes de noeuds, au sein desquels les noeuds partagent des attributs communs. Nous montrons que l'ensemble des liens conceptuels extraits à partir d'un réseau social apporte une connaissance pertinente sur les types de noeuds les plus connectés, et fournit une "vue conceptuelle" du réseau. L'efficacité de notre solution est démontrée à travers des résultats expérimentaux.
Dans ce papier, nous proposons une solution qui exploite à la fois des informations sur la structure du réseau et sur les attributs des noeuds, pour extraire un nouveau type de motifs que nous appelons "liens conceptuels". Les liens conceptuels sont des r
Paris, France

hal-00786167
https://hal.archives-ouvertes.fr/hal-00786167

Éditeur(s) : HAL CCSD Wiley
Résumé : International audience
This paper describes how to tackle new challenging coastal engineering problems related to beach erosion with a shape optimization approach. The method modifies the shape of the sea bottom in order to reduce beach erosion effects. Global optimization is shown to be necessary as the related functionals have several local minima. We describe the physical model used, the proposed protection devices against beach erosion and real case applications.
ISSN: 0029-5981

hal-00411912
https://hal.archives-ouvertes.fr/hal-00411912
DOI : 10.1002/nme.2209

Éditeur(s) : HAL CCSD Hermann-Éditions
Résumé : International audience
Cet article présente FLMin, une nouvelle méthode d'extraction de motifs fréquents dans les réseaux sociaux. Contrairement aux méthodes traditionnelles qui s'intéressent uniquement aux régularités structurelles, l'originalité de notre approche réside dans sa capacité à exploiter la structure et les attributs des noeuds pour extraire des régularités, que nous appelons "liens fréquents", dans les liens entre des noeuds partageant des caractéristiques communes.
Extraction et gestion des connaissances
Bordeaux, France

hal-00768408
https://hal.archives-ouvertes.fr/hal-00768408