Knowledge Guided Integration of Structured and Unstructured Data in Health Decision Process

Data in the health domain is continuously increasing. It is collected from several sources, has several formats and is characterized by its sensibility (protection of personal health data). These characteristics make the management and the expert interaction with the collected data, in order to facilitate decision-making in Health Information Systems (HIS) a challenging field. In this paper, we propose a Knowledge guided integration of structured and unstructured data for health decision process. The knowledge is represented by domain ontology, which allows the integration of structured and unstructured data, stored in NoSQL format. Our motivation is to combine the confirmed advantages of ontologies and NoSQL databases both in data integration and decision aided processes. The proposed ontology has been implemented and evaluated using quality metrics. The approach was evaluated and results show response time optimization, compared with traditional approaches, and improvement of data relevance

Experimental characterisation of textile compaction response: A benchmark exercise

This paper reports the results of an international benchmark exercise on the measurement of fibre bed compaction behaviour. The aim was to identify aspects of the test method critical to obtain reliable results and to arrive at a recommended test procedure for fibre bed compaction measurements. A glass fibre 2/2 twill weave and a biaxial (±45°) glass fibre non-crimp fabric (NCF) were tested in dry and wet conditions. All participants used the same testing procedure but were allowed to use the testing frame, the fixture and sample geometry of their choice. The results showed a large scatter in the maximum compaction stress between participants at the given target thickness, with coefficients of variation ranging from 38% to 58%. Statistical analysis of data indicated that wetting of the specimen significantly affected the scatter in results for the woven fabric, but not for the NCF. This is related to the fibre mobility in the architectures in both fabrics. As isolating the effect of other test parameters on the results was not possible, no statistically significant effect of other test parameters could be proven. The high sensitivity of the recorded compaction pressure near the minimum specimen thickness to changes in specimen thickness suggests that small uncertainties in thickness can result in large variations in the maximum value of the compaction stress. Hence, it is suspected that the thickness measurement technique used may have an effect on the scatter

A Society of Agents for Decision Making in Supply Chain Management

International audienc

Modélisation et Apprentissage de la Prise de Décision dans les Organisations Productives: Approche Multi-Agents

L'objectif de cette thèse est de modéliser les processus de prise de décisions dans les organisations productives en mettant l'accent sur la communication, la coopération, la négociation et surtout l'amélioration par l'apprentissage du comportement des acteurs décisionnels. Les entreprises font depuis plusieurs années des efforts importants pour étudier et développer une stratégie essentiellement orientée sur la réactivité. Cette stratégie nécessite un rapprochement entre la structure physique et la structure décisionnelle, ce qui entraîne une redistribution de la décision aux différents niveaux d'une organisation et un accroissement d'autonomie de ses acteurs décisionnels. Pour mettre en évidence cette réalité, nous insistons sur des facteurs clefs tels que la complexité des organisations productives qui sont à l'intersection de différents domaines (économique, sociologique, technologique, etc.), les mécanismes de prise de décisions distribuées, les phénomènes d'orientation de décisions, et 1' apprentissage qui est une aptitude et une faculté indispensable à tout système dynamique et évolutif. Ainsi, dans ces travaux nous proposons premièrement la modélisation des organisations productives, et en particulier de leurs processus décisionnels en se basant sur les concepts des systèmes multi-agents, deuxièmement la modélisation et la formalisation des connaissances des acteurs décisionnels, et enfin 1' apprentissage de nouvelles connaissances en we de la prise de nouvelles décisions dans des contextes ou des situations analogues en adoptant la méthode de raisonnement à partir de cas. Ces hypothèses sont validées par la construction d'une maquette de simulation qui repose sur L'iniplémentation du flux décisionnel à travers des règles de décisions et une architecture de représentation de connaissances (base de cas), et du flux physique par 1 'utilisation des techniques de simulation à événements discrets. Enfin cette maquette a été appliquée au cas d'une entreprise industrielle.No abstrac

Décision distribuée

National audienc

Optimizing OLAP Cubes Construction by Improving Data Placement on Multi-nodes Clusters

International audienceThe increasing volumes of relational data let us find an alternative to cope with them. The Hadoop framework - which isan open source project based on the MapReduce paradigm - is a popular choice for big data analytics. However, the performance gained from Hadoop’s features is currently limited by its default block placement policy, which does not take any data characteristics into account. Indeed, the efficiency of many operations can be improved by a careful data placement, including indexing, grouping, aggregation and joins. In this paper we propose a data warehouse placement policy to improve query gain performances on multi nodes clusters, especially Hadoop clusters. We investigate the performance gain for OLAP cube construction query with and without data organization. And this, by varying the number of nodes and data warehouse size. It has been found that, the proposed data placement policy has lowered global execution time for building OLAP data cubes up to 20 percent compared to default data placement

Multi-agent architecture simulation for decision making in productive organisation

International audienc

Agents intelligents et santé : entre révolution et craintes, quel avenir ?

National audienc