Éditeur(s) : Ministry of Health Ministry of Health ( Guyana )
Résumé : (Funding) Support for the development of the technical infrastructure and partner training provided by the United States Department of Education TICFIA program.
(Publication Status) The Facilitator's Guide was produced by the Ministry of Health, Guyana in April 2008. It was revised in December 2010 to include a chapter on "Sexual Health of Men Who Have Sex with Men and Gay Men" and to add time frames for the activities.

Droits : All rights reserved by the source institution.

Éditeur(s) : HAL CCSD
Résumé : International audience
Structure and evolution of networks have been areas of growing interest in recent years, especially with the emergence of Social Network Analysis (SNA) and its application in numerous fields. Researches on diffusion are focusing on network modeling for studying spreading phenomena. While the impact of network properties on spreading is now widely studied, involvement of network dynamicity is very little known. In this paper, we address the epidemiology context and study the consequences of network evolutions on spread of diseases. Experiments are conducted by comparing incidence curves obtained by evolution strategies applied on two generated and two real networks. Results are then analyzed by investigating network properties and discussed in order to explain how network evolution influences the spread. We present the MIDEN framework, an approach to measure impact of basic changes in network structure, and DynSpread, a 2D simulation tool designed to replay infections scenarios on evolving networks.
Database and Expert Systems Applications - 22nd International Conference, DEXA 2011, Toulouse, France, August 29 - September 2, 2011, Proceedings, Part II
Toulouse, France

hal-00614925
https://hal.archives-ouvertes.fr/hal-00614925
DOI : 10.1007/978-3-642-23091-2_49

Éditeur(s) : HAL CCSD Kluwer
Résumé : This paper presents some considerations about hybrid optimization algorithms useful to optimize real complex system. The given indication could be used by readers to conceive hybrid algorithms. These considerations have been deducted from a concrete application case: the satellites constellations design problem. But each of the advanced techniques proposed in this paper are considered in a more general way to solve other problems. This problem is used to illustrate the techniques along the paper because it is grouping many characteristics (di culties) of contemporary real complex systems: the size and the characteristics of the search space engendered by a combinatorial problem; The irregularity of the criterions; The mathematical and physical heterogeneity of parameters forbids the use of classical algorithms; The evaluation of a solution, which uses a time consuming simulation; A need of accurate values. More details are available in previous papers ([?], [?], [?], [?]). For these reasons, we could learn a lot from this experiment in order to detach hybrid techniques usable for problems having close characteristics. This paper presents the historic leading to the current algorithm, the modeling of the complex system and the sophisticated algorithm proposed to optimize it. Application cases and ways to built signi cant tests of hybrid algorithm are also given.
International Federation for Information Processing

hal-00602279
https://hal.archives-ouvertes.fr/hal-00602279

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
Résumé : Proceedings of the 10th International and Interdisciplinary Conference, CONTEXT 2017, Paris, France, June 20-23, 2017
International audience
This paper presents a research project in science education that is positioned at the intersection of computer science and context in learning. The main objective is to improve learning process by creating a software tool that participates, from the inception to the achievement, in the design of leaning scenarios, based on context effects, and, to show that context effects' learning is an efficient method in the development of student's knowledge regarding a concept. The software will compute differences between two – or more – external contexts based on specific parameters, related to the phenomenon or object that students are expected to study. The elaboration of the calculator (" the MazCalc ") is conducted using the design based research theory, meaning that several iterations of learning field experiments are conducted in order to collect relevant data which are used for the tool creation. In this paper, the design of the scenario involves students from North America and from the French West Indies and the concept studied is about geothermal energy. The instantiation of the context calculator is made with the geothermal object of study, and the differences are computed in the calculator between the two contexts mentioned. This example makes possible to validate the link between context effects predicted and observed, and also to study the impact of external context on the learning process. This study has been conducted thanks to the GEOTREF project support.
Modeling and Using Context

ISBN : 978-3-319-57837-8
hal-01625781
https://hal.univ-antilles.fr/hal-01625781
https://hal.univ-antilles.fr/hal-01625781/document
https://hal.univ-antilles.fr/hal-01625781/file/Elaborating%20the%20context%20calculator%20CONTEXT2017.pdf

Éditeur(s) : HAL CCSD Springer
Résumé : International audience
The study of information dissemination in social networks is of particular importance in many areas as marketing, politics and security for example. Various strategies are being developed to disseminate information, those aimed at disseminating information widely and those aimed at disseminating information in a more confidential manner to make it scarce. In this paper, we adapt a model dedicated to spreading rumours by word of mouth in a physical space to the context of social networks. We compare two modes of dissemination based on profusion or scarcity and study the impact of the choice of the initial node. The results obtained show to what extent each mode exploits the social network topology and especially the influence of hubs.
International Conference on Complex Networks and Their Applications (COMPLEX NETWORK)
Lyon, France

hal-01637573
https://hal.archives-ouvertes.fr/hal-01637573

Éditeur(s) : HAL CCSD
Résumé : International audience
Mining sequential patterns in data streams is a new challenging problem for the datamining community since data arrives sequentially in the form of continuous rapid and infinite streams. In this paper, we propose a new on-line algorithm, SPAMS, to deal with the sequential patterns mining problem in data streams. This algorithm uses an automaton-based structure to maintain the set of frequent sequential patterns, i.e. SPA (Sequential Pat- tern Automaton). The sequential pattern automaton can be smaller than the set of frequent sequential patterns by two or more orders of magnitude, which allows us to overcome the problem of combinatorial explosion of se- quential patterns. Current results can be output constantly on any user 's specified thresholds. In addition, taking into account the characteristics of data streams, we propose a well-suited method said to be approximate since we can provide near optimal results with a high probability. Experimental studies show the relevance of the SPA data structure and the efficiency of the SPAMS algorithm on various datasets. Our contribution opens a promis- ing gateway, by using an automaton as a data structure for mining frequent sequential patterns in data streams.
Advances in Knowledge Discovery and Management

lirmm-00435841
https://hal-lirmm.ccsd.cnrs.fr/lirmm-00435841
https://hal-lirmm.ccsd.cnrs.fr/lirmm-00435841/document
https://hal-lirmm.ccsd.cnrs.fr/lirmm-00435841/file/akdmSPAMS.pdf

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 Springer
Résumé : International audience
Numerous methods have been proposed in order to perform clustering from social networks. While significant works have been carried out on the design of new approaches, able to search for various kinds of clusters, a major challenge concerns the scalability of these approaches. Indeed, given the mass of data that can now be collected from online social networks, particularly from social platforms, it is important to have efficient methods for exploring and analyzing these very large amount of data. One of the recent social network clustering approaches is the extraction of conceptual links, a new approach that performs link clustering by exploiting both the structure of the network and attributes of nodes to identify strong links between groups of nodes in which nodes share common attributes. In this paper, we focus on the optimization of the search for conceptual links. In particular, we propose PALM, a parallel algorithm that aims to improve the efficiency of the extraction by simultaneously exploring several areas of the search space. For this purpose, we begin by demonstrating that the solution space forms a concept lattice. Then, we propose an approach that explores in parallel the branches of the lattice while reducing the search space based on various properties of conceptual links. We demonstrate the efficiency of the algorithm by comparing the performances with the original extraction approach. The results obtained show a significant gain on the computation time.
28th International Conference on Database and Expert Systems Applications (DEXA)
Lyon, France

hal-01637554
https://hal.archives-ouvertes.fr/hal-01637554
DOI : 10.1007/978-3-319-64471-4_21

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 Landes Bioscience
Résumé : International audience
In 2008 we published the first set of guidelines for standardizing research in autophagy. Since then, research on this topic has continued to accelerate, and many new scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Accordingly, it is important to update these guidelines for monitoring autophagy in different organisms. Various reviews have described the range of assays that have been used for this purpose. Nevertheless, there continues to be confusion regarding acceptable methods to measure autophagy, especially in multicellular eukaryotes. A key point that needs to be emphasized is that there is a difference between measurements that monitor the numbers or volume of autophagic elements (e.g., autophagosomes or autolysosomes) at any stage of the autophagic process vs. those that measure flux through the autophagy pathway (i.e., the complete process); thus, a block in macroautophagy that results in autophagosome accumulation needs to be differentiated from stimuli that result in increased autophagic activity, defined as increased autophagy induction coupled with increased delivery to, and degradation within, lysosomes (in most higher eukaryotes and some protists such as Dictyostelium) or the vacuole (in plants and fungi). In other words, it is especially important that investigators new to the field understand that the appearance of more autophagosomes does not necessarily equate with more autophagy. In fact, in many cases, autophagosomes accumulate because of a block in trafficking to lysosomes without a concomitant change in autophagosome biogenesis, whereas an increase in autolysosomes may reflect a reduction in degradative activity. Here, we present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macroautophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes. These guidelines are not meant to be a formulaic set of rules, because the appropriate assays depend in part on the question being asked and the system being used. In addition, we emphasize that no individual assay is guaranteed to be the most appropriate one in every situation, and we strongly recommend the use of multiple assays to monitor autophagy. In these guidelines, we consider these various methods of assessing autophagy and what information can, or cannot, be obtained from them. Finally, by discussing the merits and limits of particular autophagy assays, we hope to encourage technical innovation in the field.
Autophagy

hal-00735751
https://hal.archives-ouvertes.fr/hal-00735751
PUBMED : 22966490