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42 results on '"Dervaux, Stéphane"'

4. Learning Probabilistic Relational Models Using an Ontology of Transformation Processes

Author

Munch, Melanie, Wuillemin, Pierre-Henri, Manfredotti, Cristina, Dibie, Juliette, Dervaux, Stephane, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Panetto, Hervé, editor, Debruyne, Christophe, editor, Gaaloul, Walid, editor, Papazoglou, Mike, editor, Paschke, Adrian, editor, Ardagna, Claudio Agostino, editor, and Meersman, Robert, editor

Published
2017
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5. - A Process and Observation Ontology in Food Science. Application to Dairy Gels

Author

Ibanescu, Liliana, Dibie, Juliette, Dervaux, Stéphane, Guichard, Elisabeth, Raad, Joe, Diniz Junqueira Barbosa, Simone, Series editor, Chen, Phoebe, Series editor, Du, Xiaoyong, Series editor, Filipe, Joaquim, Series editor, Kara, Orhun, Series editor, Kotenko, Igor, Series editor, Liu, Ting, Series editor, Sivalingam, Krishna M., Series editor, Washio, Takashi, Series editor, Garoufallou, Emmanouel, editor, Subirats Coll, Imma, editor, Stellato, Armando, editor, and Greenberg, Jane, editor

Published
2016
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6. – A Multi-scale and Multi-step Ontology for Transformation Processes: Application to Micro-Organisms

Author

Dibie, Juliette, Dervaux, Stéphane, Doriot, Estelle, Ibanescu, Liliana, Pénicaud, Caroline, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Josef, Kittler, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Haemmerlé, Ollivier, editor, Stapleton, Gem, editor, and Faron Zucker, Catherine, editor

Published
2016
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11. Biocomposites from poly(3-hydroxybutyrate-co-3-hydroxyvalerate) and lignocellulosic fillers: Processes stored in data warehouse structured by an ontology

Author

Munch, Mélanie, primary, Buche, Patrice, additional, Dervaux, Stéphane, additional, Breysse, Amélie, additional, Berthet, Marie-Alix, additional, David, Grégoire, additional, Lammi, Sarah, additional, Rol, Fleur, additional, Viretto, Amandine, additional, and Angellier-Coussy, Hélène, additional

Published
2022
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12. Biocomposites from poly(3-hydroxybutyrate-co-3-hydroxyvalerate) and lignocellulosic fillers: Processes stored in data warehouse structured by an ontology

Author

Munch, Mélanie, Buche, Patrice, Dervaux, Stéphane, Breysse, Amélie, Berthet, Marie-Alix, David, Grégoire, Lammi, Sarah, Rol, Fleur, Viretto, Amandine, Angellier-Coussy, Hélène, Munch, Mélanie, Buche, Patrice, Dervaux, Stéphane, Breysse, Amélie, Berthet, Marie-Alix, David, Grégoire, Lammi, Sarah, Rol, Fleur, Viretto, Amandine, and Angellier-Coussy, Hélène

Abstract

Due to the rising amount of plastic waste generated each year, multiple questions are emerging about their harmful long-term effects on the environment, the eco-systems and human health. One possible strategy to mitigate these issues is to substitute conventional plastics by materials fully biodegradable in natural conditions, such as poly(3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBV). In order to decrease the overall cost and environmental impact of PHBV-based materials while modulating their technical performance, PHBV can be combined with lignocellulosic fillers. In this article, a total of 88 formulations of PHBV-based biocomposites has been collected, distributed over 5 interdisciplinary projects involving computer scientists, data scientists and biomass processing experts for food and bio-based material production. Available data concern the technical process descriptions, including the description of each step and the different observations measured.

Published
2022

13. Food ontologies

Author

Tamma, V., Castellano-Escuder, Pol, González-Domínguez, Raúl, Wishart, David S, Andrés-Lacueva, Cristina, Sánchez-Pla, Alex, Snae, Chakkrit, Bruckner, Michael, Pizzuti, T., Mirabelli, G., Dragoni, M., Bailoni, Tania, Maimone, Rosa, Eccher, C., Vitali, F., Lombardo, Rosario, Rivero, Damaríz, Mattivi, F., Franceschi, P., Bordoni, A., Trimigno, Alessia, Capozzi, F., Felici, G., Taglino, F., Miglietta, F., De Cock, N., Lachat, C., De Baets, B., De Tré, G., Pinart, M., Nimptsch, K., Pischon, T., Bouwman, J., Cavalieri, D., Eftimov, T., Ispirova, Gordana, Potočnik, Doris, Ogrinc, N., Seljak, B. Koroušić, Jiomekong, Azanzi, Caracciolo, Caterina, Morshed, Ahsan, Stellato, Armando, Johannsen, Gudrun, Jaques, Yves, Keizer, Johannes, Cordier, Amélie, Dufour-Lussier, Valmi, Lieber, Jean, Nauer, Emmanuel, Badra, Fadi, Cojan, Julien, Gaillard, Emmanuelle, Infante-Blanco, Laura, Molli, Pascal, Napoli, Amedeo, Skaf-Molli, Hala, Karim, Shakir, Shaikh, Umair Uddin, Rajput, Quratulain, Asif, Zaheeruddin, Çelik, Duygu, Kolchin, Maxim, Chistyakov, A., Lapaev, Maxim, Khaydarova, R., Ibanescu, Liliana, Dibie, Juliette, Dervaux, Stéphane, Guichard, Elisabeth, Raad, Joe, Eftimov, Tome, Korošec, Peter, Seljak, Barbara Koroušić, Pizzuti, Teresa, Mirabelli, Giovanni, Grasso, Giovanni, Paldino, Giulia, Wang, Hongwei, Zhang, Fuzheng, Wang, Jialin, Zhao, Miao, Li, Wenjie, Xie, Xing, Guo, Minyi, Sherimon, Vinu, P.C, Sherimon, Ismaeel, Alaa, Varkey, Winny, B, Naveen, Padhiar, Ishita, Seneviratne, O., Chari, Shruthi, Gruen, Daniel, and McGuinness, D.

Subjects
Semantic Web
Abstract

A review of: - Methodologies, methods and tools used for the construction and evaluation of food ontologies - Integration of food ontologies in real world application to solve real world problems

Published
2022
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14. Alignement et enrichissement d’ontologies utilisées par deux systèmes d’informations gérant des données expérimentales sur les procédés de transformation : OpenSILEX-EnviBIS et PO2 BaGaTel

Author

Fernandez, Emilie, Weber, Magalie, Buche, Patrice, Cufi, Julien, Dervaux, Stéphane, Ibanescu, Liliana, Latrille, Eric, Neveu, Pascal, Rossard, Virginie, Tireau, Anne, and Weber, Magalie

Subjects
OpenSILEX-EnviBIS, données expérimentales, [INFO] Computer Science [cs], PO2 BaGaTel
Published
2022

18. How to Manage Incompleteness of Nutritional Food Sources?: A solution using FoodOn as pivot ontology

Author

Buche, Patrice, Cufi, Julien, Dervaux, Stéphane, Dibie, Juliette, Ibanescu, Liliana, Oudot, Alrick, Weber, Magalie, Ingénierie des Agro-polymères et Technologies Émergentes (UMR IATE), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Université de Montpellier (UM)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Mathématiques et Informatique Appliquées (MIA-Paris), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-AgroParisTech-Université Paris-Saclay, Unité de recherche sur les Biopolymères, Interactions Assemblages (BIA), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), and FUI Metyl@b Project financed by BPI France

Subjects
Ontology Alignment, Ontology Building, Incompleteness Management, Background Knowledge, LanguaL, [INFO]Computer Science [cs], FoodOn, ANSES, USDA, Food Composition Databases
Abstract

International audience; In order to correctly assess the nutritional quality of a raw or manufactured food product, the first step is to obtain the associated nutritional values. Food composition databases (FCDBs) managed at national level provide values for nutrients of foods. Unfortunately, values associated with some nutrients of interest may be lacking in the FCDB of the country in which the nutritional quality must be assessed and finding values associated with nutrients for similar foods in other FCDBs is a way to deal with incompleteness. An additional issue arises because the vocabulary used to denote a given food in a given FCDB is usually different from the one used in others. In this paper, the authors address the problem of retrieving the nutritional value of foods by querying different FCDBs through FoodOn used as pivot ontology. The article presents a new food source alignment method between two FCDBs. The method has been evaluated on the French and United States food nutritional evaluation. The proposed solution for the incompleteness management task has been assessed with a real use case.

Published
2021
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19. Global Plant Extinction Risk Assessment Inform Novel Biodiversity Hotspots

Author

Haevermans, Thomas, primary, Tressou, Jessica, additional, Kwon, Joon, additional, Pellens, Roseli, additional, Dubéarnès, Anne, additional, Veron, Simon, additional, Bel, Liliane, additional, Dervaux, Stéphane, additional, Dibie-Barthelemy, Juliette, additional, Gaudeul, Myriam, additional, Govaerts, Rafaël, additional, Le Bras, Gwenaël, additional, Muller, Serge, additional, Rouhan, Germinal, additional, Sarthou, Corinne, additional, and Soler, Lydie, additional

Published
2021
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21. A new alignment method based on FoodOn as pivot ontology to integrate nutritional legacy data sources

Author

Buche, Patrice, Cufi, Julien, Dervaux, Stéphane, Dibie, Juliette, Ibanescu, Liliana, Oudot, Alrick, Weber, Magalie, Ingénierie des Agro-polymères et Technologies Émergentes (UMR IATE), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Université de Montpellier (UM)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Graphs for Inferences on Knowledge (GRAPHIK), Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier (LIRMM), Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Mathématiques et Informatique Appliquées (MIA-Paris), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-AgroParisTech-Université Paris-Saclay, Unité de recherche sur les Biopolymères, Interactions Assemblages (BIA), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Ibanescu, Liliana, Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Université de Montpellier (UM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro - Montpellier SupAgro, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Inria Sophia Antipolis - Méditerranée (CRISAM), Mathématiques et Informatique Appliquées (MIA Paris-Saclay), and AgroParisTech-Université Paris-Saclay-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)

Subjects
Ontology alignment, LanguaL, [INFO]Computer Science [cs], Food composition databases, [INFO] Computer Science [cs], FoodOn
Abstract

International audience; In order to correctly assess the nutritional quality of a meal or a manufactured food product in a given country, the first step is to assess the nutritional values for its ingredients. Food composition databases (FCDBs) available in a lot of countries and managed at national level provide values for energy and nutrients of food components. Unfortunately, values associated with some nutrients of interest may be lacking in the FCDB of the country in which the nutritional quality must be assessed. Finding values associated with nutrients for similar foods in other FCDBs is a way to deal with incompleteness. An additional issue arises because the vocabulary used to describe the ingredients of a meal or a recipe in a given FCDB is usually different from the one used in other ones. In this paper we address the problem of identifying the nutritional value of recipe's ingredients by querying different FCDBs through FoodOn as pivot ontology. We present a new alignment method between two distinct FCDBs, based on syntactic and semantic approaches, whose vocabulary is previously transformed into an ontology. Our method has been evaluated on Ciqual, the French food nutritional database, USDA, the United States food nutritional database and the FoodOn ontology. The incompleteness management task based on FoodOn as pivot ontology has been assessed with a real use-case concerning iron, Vitamin B12, Vitamin C nutrients.

Published
2020

22. Food transformation process description using PO2 and FoodOn

Author

Buche, Patrice, Cufi, Julien, Dervaux, Stéphane, Dibie, Juliette, Ibanescu, Liliana, Oudot, Alrick, Weber, Magalie, Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier (LIRMM), Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS), Graphs for Inferences on Knowledge (GRAPHIK), Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Ingénierie des Agro-polymères et Technologies Émergentes (UMR IATE), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Université de Montpellier (UM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro - Montpellier SupAgro, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Mathématiques et Informatique Appliquées (MIA Paris-Saclay), AgroParisTech-Université Paris-Saclay-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Unité de recherche sur les Biopolymères, Interactions Assemblages (BIA), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Ibanescu, Liliana, Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Université de Montpellier (UM)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Mathématiques et Informatique Appliquées (MIA-Paris), and Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-AgroParisTech-Université Paris-Saclay

Subjects
[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI], ontology ecosystem, observation, semantic integration, food transformation process, domain ontology, food component modeling, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]
Abstract

International audience; The food production and processing sector are facing sustainability challenges of growing complexity. To tackle these challenges, data and knowledge from many different domains may be structured and stored using an ontol-ogy, a semantic model. In this paper we present a core ontology designed to model processes and observations from food domains. Three datasets struc-tured according with this ontology are stored into a repository. Dedicated tools were designed to assist domain experts in integrating and querying data. Semantic integration of data from food transformation domains may enable new decision support tools for new products with good qualities and eco-friendly properties.

Published
2020

24. A use ase of data integration in food production

Author

Ibanescu, Liliana, Allard, Thomas, Dervaux, Stéphane, Dibie, Juliette, Guichard, Elisabeth, Pénicaud, Caroline, Raad, Joe, UMR : Mathématiques et Informatique Appliquées, Paris, Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), Centre des Sciences du Goût et de l'Alimentation [Dijon] (CSGA), Institut National de la Recherche Agronomique (INRA)-Université de Bourgogne (UB)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Centre National de la Recherche Scientifique (CNRS), Université Bourgogne Franche-Comté [COMUE] (UBFC), Génie et Microbiologie des Procédés Alimentaires (GMPA), Institut National de la Recherche Agronomique (INRA)-AgroParisTech, This work was supported by the Qualiment Carnot Institute of the French National, and Research Agency through the NutriSensAl project (grant number 16CARN002601) and by the Saclay Data Center through the LIONES project.

Subjects
ontology based data integration, process representation, experimental observations representation, food science, [SDV.AEN]Life Sciences [q-bio]/Food and Nutrition
Abstract

This paper presents a use case about knowledge representation and integration of data from different domains in food science. An ontology named PO2DG, the Process and Observation Ontology for the production of Dairy Gels, has been designed in order to provide a shared vocabulary for domain experts. The available data have been semantically structured using PO2DG and are stored in an RDF repository named PO2DG dataset. This use case identifies some of the challenges when dealing with a multi domain representation problem, gives some hints about possible solutions and suggests some further work.

Published
2018

25. PO2 VocabularyManager - A Collaborative Tool to Assist Users in Building a PO2 Domain Ontology Linked with Existing Resources

Author

Dervaux, Stéphane, Ibanescu, Liliana, Dibie-Barthelemy, Juliette, Mathématiques et Informatique Appliquées (MIA-Paris), and AgroParisTech-Institut National de la Recherche Agronomique (INRA)

Subjects
ACM: H.: Information Systems/H.3: INFORMATION STORAGE AND RETRIEVAL/H.3.3: Information Search and Retrieval, ACM: H.: Information Systems, ACM: H.: Information Systems/H.3: INFORMATION STORAGE AND RETRIEVAL, [INFO.INFO-WB]Computer Science [cs]/Web, [INFO]Computer Science [cs], ComputingMilieux_MISCELLANEOUS, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]
Abstract

International audience

Published
2018

26. Computer-based tailored dietary counselling improves the nutrient adequacy of the diet of French pregnant women: a randomised controlled trial

Author

Bianchi, Clélia M., primary, Mariotti, François, additional, Lluch, Anne, additional, Journet, Claire, additional, Stehr, Yaëlle, additional, Beaussier, Hélène, additional, Fournier, Julien, additional, Dervaux, Stéphane, additional, Cohen-Tanuggi, Dylan, additional, Reulet, Elodie, additional, Verger, Eric O., additional, Azria, Elie, additional, and Huneau, Jean-François, additional

Published
2019
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28. [MS]²O: A Multi-scale and Multi-step Ontology for Transformation Processes: Application to Micro-Organisms

Author

Dibie, Juliette, Dervaux, Stéphane, DORIOT, Estelle, Ibanescu, Liliana, Pénicaud, Caroline, Mathématiques et Informatique Appliquées (MIA-Paris), AgroParisTech-Institut National de la Recherche Agronomique (INRA), Génie et Microbiologie des Procédés Alimentaires (GMPA), Institut National de la Recherche Agronomique (INRA)-AgroParisTech, Mathématiques et Informatique Appliquées ( MIA-Paris ), Institut National de la Recherche Agronomique ( INRA ) -AgroParisTech, and Génie et Microbiologie des Procédés Alimentaires ( GMPA )

Subjects
[ INFO ] Computer Science [cs], domain ontology building, [INFO]Computer Science [cs], transformation processes, ComputingMilieux_MISCELLANEOUS, multi-step and multi-scale on- tology
Abstract

International audience; This paper focuses on the knowledge representation for an interdisciplinary project concerning transformation processes in food science. The use case concerns the production of stabilized microorganisms performed at INRA (French National Institute for Agricultural Research). Experimental observations are available for some inputs of the production processes, at different steps and at a certain scale. Available data sets are described using different vocabularies and are stored in different formats. Therefore there is a need to define an ontology, called [M S] 2 O, as a common and standardized vocabulary. Users' requirements were defined through competency questions and the ontology was validated against these competency questions. [M S] 2 O ontology aims to play a key role as the representation layer of the querying and simulation systems of the project. This leads to the possibility of comparing different production scenarios and suggesting improvements.

Published
2016
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29. MAP-OPT: A software for supporting decision-making in the field of modified atmosphere packaging of fresh non respiring foods

Author

Guillard, Valérie, primary, Couvert, Olivier, additional, Stahl, Valérie, additional, Buche, Patrice, additional, Hanin, Aurélie, additional, Denis, Catherine, additional, Dibie, Juliette, additional, Dervaux, Stéphane, additional, Loriot, Catherine, additional, Vincelot, Thierry, additional, Huchet, Véronique, additional, Perret, Bruno, additional, and Thuault, Dominique, additional

Published
2017
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30. Computer-based tailored dietary counselling improves the nutrient adequacy of the diet of French pregnant women: a randomised controlled trial.

Author

Bianchi, Clélia M., Mariotti, François, Lluch, Anne, Journet, Claire, Stehr, Yaëlle, Beaussier, Hélène, Fournier, Julien, Dervaux, Stéphane, Cohen-Tanuggi, Dylan, Reulet, Elodie, Verger, Eric O., Azria, Elie, and Huneau, Jean-François

Subjects
ALGORITHMS, COUNSELING, DIET, PATIENT aftercare, INTERNET, MATERNAL health services, COMPUTERS in medicine, NUTRITIONAL requirements, PAMPHLETS, THERAPEUTICS, WOMEN'S health, RANDOMIZED controlled trials, FOOD diaries, DESCRIPTIVE statistics, PREGNANCY
Abstract

During pregnancy, mothers-to-be should adapt their diet to meet increases in nutrient requirements. Pregnant women appear to be keener to adopt healthier diets, but are not always successful. The objective of the present study was to determine whether a guided, stepwise and tailored dietary counselling programme, designed using an optimisation algorithm, could improve the nutrient adequacy of the diet of pregnant women, beyond generic guidelines. Pregnant women (n 80) who attended Notre-Dame-de-Bon-Secours Maternity Clinic were randomly allocated to the control or intervention arm. Dietary data were obtained twice from an online 3-d dietary record. The nutrient adequacy of the diet was calculated using the PANDiet score, a 100-point diet quality index adapted to the specific nutrient requirements for pregnancy. Women were supplied with generic dietary guidelines in a reference booklet. In the intervention arm, they also received nine sets of tailored dietary advice identified by an optimisation algorithm as best improving their PANDiet score. Pregnant women (n 78) completed the 12-week dietary follow-up. Initial PANDiet scores were similar in the control and intervention arms (60·4 (sd 7·3) v. 60·3 (sd 7·3), P = 0·92). The PANDiet score increased in the intervention arm (+3·6 (sd 9·3), P = 0·02) but not in the control arm (−0·3 (sd 7·3), P = 0·77), and these changes differed between arms (P = 0·04). In the intervention arm, there were improvements in the probabilities of adequacy for α -linolenic acid, thiamin, folate and cholesterol intakes (P < 0·05). Tailored dietary counselling using a computer-based algorithm is more effective than generic dietary counselling alone in improving the nutrient adequacy of the diet of French women in mid-pregnancy. [ABSTRACT FROM AUTHOR]

Published
2020
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32. Utilisation d'un outil de recherche d'information pour la mise en correspondance de thesaurus. Application aux sciences du vivant

Author

Planes, Laurie, Dervaux, Stéphane, Dibie-Barthelemy, Juliette, Guinet, Nicolas, Ibanescu, Liliana, Méthodologies d'Analyse de Risque Alimentaire (MET@RISK), Institut National de la Recherche Agronomique (INRA), AgroParisTech, Alimentation et Sciences Sociales, and Session : Poster

Subjects
application aux sciences du vivant, étiquetage, outil de recherche d'information, mise en correspondance de thesaurus, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]
Abstract

International audience; Nous présentons dans cet article un outil d'étiquetage de plusieurs thesaurus afin d'aider des experts ayant des besoins différents à les mettre en correspondance. L'étiquetage des différents thesaurus, appelés thesaurus sources, est effectué à l'aide d'un thesaurus pivot. Il consiste à étique-ter chaque élément des thesaurus sources le plus largement possible avec des éléments du thesaurus pivot, ceci afin de prendre en compte les besoins des différents experts. Nous proposons de considérer la tâche d'étiquetage comme un problème de recherche d'information où chaque élément d'un thesaurus source est considéré comme une requête et chaque élément du thesaurus pivot comme un document sur lequel sera projeté la requête. Une expérimentation dans le cadre de la plateforme du Pôle Alimentation Parisien (PAP), permettant le traitement et l'exploitation de sources de données hétérogènes dans le domaine de l'Alimentation et de la Santé, est présentée.

Published
2013

33. Semi-Automatic Loading of a Microbial Risk in Food Database Thanks to a Domain Ontology

Author

Buche, Patrice, Dervaux, Stéphane, Dibie-Barthelemy, Juliette, Ibanescu, Liliana, Soler, Lydie, Ingénierie des Agro-polymères et Technologies Émergentes (UMR IATE), Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Université Montpellier 2 - Sciences et Techniques (UM2)-Université de Montpellier (UM)-Institut National de la Recherche Agronomique (INRA), Graphs for Inferences on Knowledge (GRAPHIK), Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier (LIRMM), Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Méthodologies d'Analyse de Risque Alimentaire (MET@RISK), Institut National de la Recherche Agronomique (INRA), AgroParisTech, Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Université Montpellier 2 - Sciences et Techniques (UM2)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Université de Montpellier (UM)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), and Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Inria Sophia Antipolis - Méditerranée (CRISAM)

Subjects
[INFO.INFO-WB]Computer Science [cs]/Web, data and knowledge capitalization, ontology, data annotation
Abstract

INFO/GraphIKINFO:INFO_WBhttp://www.effostconference.com/non spécifiéePosterMontpellierFrance; International audience; A preliminary step in microbial risk assessment in food is to gather and to capitalize experimental data. We have designed, in the predictive modeling platform Sym'Previus (www.symprevius.org), a relational database, MicroRisk-RDB, to store experimental data in microbial risk. Those data are used as required input parameters of pathogen germs growth simulation models. Data capitalization task encounters a challenging lock. Indeed, original data are spread out in heterogeneous data sources (scientific papers, technical reports / sheets, PhD thesis ...). Moreover, they are expressed in heterogeneous formats (mainly tables, text and graphics) and vocabularies. Manual entering of data in a database (e.g. MicroRisk-RDB) is therefore a time-consuming task and developing methods and tools to facilitate data capitalization are required. In the French ANR project MAP'OPT (Equilibrium Gas Composition in Modified Atmosphere Packaging and Food Quality), we are currently designing a semi-automatic tool, @Web-Tool, to facilitate the loading of MicroRisk-RDB. Data stored in MicroRisk-RDB are indexed using a predefined vocabulary (called ontology in the following), MicroRisk-Onto, organized as a taxonomy. This ontology is re-used in @Web-Tool to facilitate the loading of the database. @Web-Tool is a semi-automatic tool, under development, designed to help domain experts to load MicroRisk-RDB from data tables found in scientific publications, especially on the Web. We focus on data tables as they often contain a synthesis of experimental results published in scientific publications. The user downloads an HTML scientific document, then data tables are automatically identified and extracted from the document and a graphical user-friendly interface, based on MicroRisk-Onto, helps the user to extract pertinent information from selected data tables and to load them in MicroRisk-RDB. @Web-Tool is designed as a generic semantic Web tool allowing any database to be loaded assuming that there exists an ontology describing the application domain.

Published
2012

42. Conception du conditionnement d'aliments sous atmosphère modifiée.

Author

THUAULT, Dominique, CHAIX, Estelle, TOUHAMI, Rim, HUCHET, Véronique, BUCHE, Patrice, DIBIE, Juliette, LECLUSE, Maxime, COULON, Florence, LORIOT, Catherine, VINCELOT, Thierry, STAHL, Valérie, DENIS, Catherine, HANIN, Aurelie, COUVERT, Olivier, DERVAUX, Stéphane, and GUILLARD, Valérie

Abstract

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Published
2015

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