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Samuel J.,CNRS Laboratory of Images and Information Systems Information Technology | Rey C.,CNRS Laboratory of Informatics, Modeling and Optimization of Systems
2016 11th International Conference on Digital Information Management, ICDIM 2016 | Year: 2016

The use of diverse web services has simplified routine tasks but it has resulted in loss of direct control over the data. This shift from traditional self-controlled databases to heterogeneous, autonomous web services can be increasingly seen among small and medium scale enterprises. Enterprises dependent on web services require a generic approach to integrate with multiple web services. The classical mediation approach from the data integration field provides a uniform query interface to diverse data sources hiding the underlying heterogeneity, but its utilization with current generation web services API has several research and industrial challenges which will be described in this article. © 2016 IEEE.


Lemmouchi S.,University Claude Bernard Lyon 1 | Haddad M.,CNRS Laboratory of Images and Information Systems Information Technology | Kheddouci H.,University Claude Bernard Lyon 1
Computer Communications | Year: 2013

The study of emerged community structure is an important challenge in networks analysis. In fact, several methods have been proposed in the literature to statistically determine the significance of discovered structures. Nevertheless, most of existing analysis models consider only the structural aspect of emerged communities. We are interested in studying the robustness of emerged communities in peer-to-peer (P2P) networks. More precisely, we consider the emerged communities in the induced graph by all the exchanges in these networks. Hence, rather than examining the robustness only on the structural properties of the graph, we will focus on the parameters that allow the emergence of community structures. In fact, perturbing these parameters might destroy most of the obtained properties at the emerged level. To the best of our knowledge, robustness of networks has never been considered from this angle before. In this paper, we study the impact of perturbing the content and the profile of nodes on the emerged communities in P2P networks. We show how these alterations affect both structure and information supported by the emerged structures. © 2013 Elsevier B.V. All rights reserved.


Bulbul A.,Bilkent University | Capin T.,Bilkent University | Lavoue G.,INSA Lyon | Lavoue G.,CNRS Laboratory of Images and Information Systems Information Technology | Preda M.,Orange Group
IEEE Signal Processing Magazine | Year: 2011

Recent advances in evaluating and measuring the perceived visual quality of three-dimensional (3-D) polygonal models are presented in this article, which analyzes the general process of objective quality assessment metrics and subjective user evaluation methods and presents a taxonomy of existing solutions. Simple geometric error computed directly on the 3-D models does not necessarily reflect the perceived visual quality; therefore, integrating perceptual issues for 3-D quality assessment is of great significance. This article discusses existing metrics, including perceptually based ones, computed either on 3-D data or on two-dimensional (2-D) projections, and evaluates their performance for their correlation with existing subjective studies. © 2011 IEEE.


Andres E.,University of Poitiers | Roussillon T.,CNRS Laboratory of Images and Information Systems Information Technology
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2011

In this paper we propose an analytical description of different kinds of digital circles that appear in the literature and especially in digital circle recognition algorithms. © 2011 Springer-Verlag.


Berry H.,French Institute for Research in Computer Science and Automation | Berry H.,CNRS Laboratory of Images and Information Systems Information Technology | Chate H.,CEA Saclay Nuclear Research Center
Physical Review E - Statistical, Nonlinear, and Soft Matter Physics | Year: 2014

In vivo measurements of the passive movements of biomolecules or vesicles in cells consistently report "anomalous diffusion," where mean-squared displacements scale as a power law of time with exponent α<1 (subdiffusion). While the detailed mechanisms causing such behaviors are not always elucidated, movement hindrance by obstacles is often invoked. However, our understanding of how hindered diffusion leads to subdiffusion is based on diffusion amidst randomly located immobile obstacles. Here, we have used Monte Carlo simulations to investigate transient subdiffusion due to mobile obstacles with various modes of mobility. Our simulations confirm that the anomalous regimes rapidly disappear when the obstacles move by Brownian motion. By contrast, mobile obstacles with more confined displacements, e.g., Orstein-Ulhenbeck motion, are shown to preserve subdiffusive regimes. The mean-squared displacement of tracked protein displays convincing power laws with anomalous exponent α that varies with the density of Orstein-Ulhenbeck (OU) obstacles or the relaxation time scale of the OU process. In particular, some of the values we observed are significantly below the universal value predicted for immobile obstacles in two dimensions. Therefore, our results show that subdiffusion due to mobile obstacles with OU type of motion may account for the large variation range exhibited by experimental measurements in living cells and may explain that some experimental estimates are below the universal value predicted for immobile obstacles. © 2014 American Physical Society.


Duchateau F.,CNRS Laboratory of Images and Information Systems Information Technology
DATA 2013 - Proceedings of the 2nd International Conference on Data Technologies and Applications | Year: 2013

The Web 2.0 and the inexpensive cost of storage have pushed towards an exponential growth in the volume of collected and produced data. However, the integration of distributed and heterogeneous data sources has become the bottleneck for many applications, and it therefore still largely relies on manual tasks. One of this task, named matching or alignment, is the discovery of correspondences, i.e., semantically-equivalent elements in different data sources. Most approaches which attempt to solve this challenge face the issue of deciding whether a pair of elements is a correspondence or not, given the similarity value(s) computed for this pair. In this paper, we propose a generic and flexible framework for selecting the correspondences by relying on the discriminative similarity values for a pair. Running experiments on a public dataset has demonstrated the im-provment in terms of quality and the robustness for adding new similarity measures without user intervention for tuning.


Elghazel H.,University of Lyon | Elghazel H.,CNRS Laboratory of Images and Information Systems Information Technology | Aussem A.,University of Lyon | Aussem A.,CNRS Laboratory of Images and Information Systems Information Technology
Machine Learning | Year: 2013

In this paper, we show that the way internal estimates are used to measure variable importance in Random Forests are also applicable to feature selection in unsupervised learning. We propose a new method called Random Cluster Ensemble (RCE for short), that estimates the out-of-bag feature importance from an ensemble of partitions. Each partition is constructed using a different bootstrap sample and a random subset of the features. We provide empirical results on nineteen benchmark data sets indicating that RCE, boosted with a recursive feature elimination scheme (RFE) (Guyon and Elisseeff, Journal of Machine Learning Research, 3:1157–1182, 2003), can lead to significant improvement in terms of clustering accuracy, over several state-of-the-art supervised and unsupervised algorithms, with a very limited subset of features. The method shows promise to deal with very large domains. All results, datasets and algorithms are available on line (http://perso.univ-lyon1.fr/haytham.elghazel/RCE.zip). © 2013, The Author(s).


Mandin S.,CNRS Laboratory of Images and Information Systems Information Technology
Proceedings - IEEE 14th International Conference on Advanced Learning Technologies, ICALT 2014 | Year: 2014

Our aim is to improve the summary activity and the understanding of texts. We design a TEL environment, Resum'Web, which we present to grade 10 students. It delivers feedback, not necessarily correct, on two tasks: 1) selection of important sentences and 2) identification of type of produced sentences. The system appears to benefit the first task and the produced sentences distribution when the important sentences of a text are more salient. However, we do not observe any effect on the first task nor on the understanding. © 2014 IEEE.


Soula H.,French Institute for Research in Computer Science and Automation | Soula H.,French Institute of Health and Medical Research | Care B.,French Institute for Research in Computer Science and Automation | Care B.,French Institute of Health and Medical Research | And 4 more authors.
Biophysical Journal | Year: 2013

Measurements of protein motion in living cells and membranes consistently report transient anomalous diffusion (subdiffusion) that converges back to a Brownian motion with reduced diffusion coefficient at long times after the anomalous diffusion regime. Therefore, slowed-down Brownian motion could be considered the macroscopic limit of transient anomalous diffusion. On the other hand, membranes are also heterogeneous media in which Brownian motion may be locally slowed down due to variations in lipid composition. Here, we investigate whether both situations lead to a similar behavior for the reversible ligand-binding reaction in two dimensions. We compare the (long-time) equilibrium properties obtained with transient anomalous diffusion due to obstacle hindrance or power-law-distributed residence times (continuous-time random walks) to those obtained with space-dependent slowed-down Brownian motion. Using theoretical arguments and Monte Carlo simulations, we show that these three scenarios have distinctive effects on the apparent affinity of the reaction. Whereas continuous-time random walks decrease the apparent affinity of the reaction, locally slowed-down Brownian motion and local hindrance by obstacles both improve it. However, only in the case of slowed-down Brownian motion is the affinity maximal when the slowdown is restricted to a subregion of the available space. Hence, even at long times (equilibrium), these processes are different and exhibit irreconcilable behaviors when the area fraction of reduced mobility changes. © 2013 Biophysical Society.


Elghazel H.,CNRS Laboratory of Images and Information Systems Information Technology | Benabdeslem K.,CNRS Laboratory of Images and Information Systems Information Technology
Neural Processing Letters | Year: 2014

Self-organizing map (SOM) is an artificial neural network tool that is trained using unsupervised learning to produce a low dimensional representation of the input space, called a map. This map is generally the object of a clustering analysis step which aims to partition the referents vectors (map neurons) into compact and well-separated groups. In this paper, we consider the problem of the clustering SOM using different aspects: partitioning, hierarchical and graph coloring based techniques. Unlike the traditional clustering SOM techniques, which use k-means or hierarchical clustering, the graph-based approaches have the advantage of providing a partitioning of the SOM by simultaneously using dissimilarities and neighborhood relations provided by the map. We present the experimental results of several comparisons between these different ways of clustering. © 2013 Springer Science+Business Media New York.

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