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5,860 results on '"St Etienne"'

1. TCT-185 Safety and Performance Registry for an All-Comers Subject Population With the Limus-Eluting Orsiro Mission Stent System Within Daily Clinical Practice: 12-Month Results of the BIOFLOW-VIII Registry

Author: Barragan, Paul, primary, Maillard, Luc, additional, Morel, Olivier, additional, Delarche, Nicolas, additional, de Poli, Fabien, additional, Morelle, Jean-François, additional, Lesault, Pierre-François, additional, Tirouvanziam, Ashok, additional, Biron, Yves, additional, St Etienne, Christophe, additional, Range, Gregoire, additional, Lhoest, Nicolas, additional, Jeanneteau, Julien, additional, Quaino, Gonzalo, additional, Bellemain, Anne, additional, Digne, Franck, additional, Chapon, Philippe, additional, Fradi, Sahbi, additional, Boueri, Ziad, additional, Rosencher, Julien, additional, Labeque, Jean-Noel, additional, Abdellaoui, Mohamed, additional, Piot, Christophe, additional, Filippi, Emmanuelle, additional, Petroni, Thibaut, additional, Shayne, John, additional, Austruy, Julien, additional, Robin, Christophe, additional, Brimont, Olivier, additional, Boukantar, Madjid, additional, Lafont, Alexandre, additional, Bourkaib, Ryad, additional, Decoulx, Eric, additional, Valy, Yann, additional, Motreff, Pascal, additional, Staat, Patrick, additional, Valla, Matthieu, additional, Durand, Philippe, additional, Colin, Patrice, additional, Pouillot, Christophe, additional, Goube, Pascal, additional, Vrolix, Mathias, additional, and Lattuca, Benoit, additional
Published: 2023
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2. Une stratégie européenne de policy mix pour les années 2000

Author: SAINT-ETIENNE, Christian and St Etienne, Christian
Published: 1999

3. LETTRES DE RABAUT SAINT-ÉTIENNE

Author: de St-Étienne, Rabaut and Rabaut, J.-P.
Published: 1885

4. Development of Micro‐Pattern Gas Detectors Technologies

Author: Peskov, Vladimir, St, Etienne, Riegler, Werner, Ropelewski, Leszek, Sauli, Fabio, and Tera
Published: 2008
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5. Une démarche qualité à l’université

Author: Louvain School of Management - Operations and Information, Université St Etienne - FUCaM autre, FUCAM - Sciences de gestion, Ahues, Mario, Meskens, Nadine, Carrion, Fabian, 26 ème congrès de l'AIPU, Louvain School of Management - Operations and Information, Université St Etienne - FUCaM autre, FUCAM - Sciences de gestion, Ahues, Mario, Meskens, Nadine, Carrion, Fabian, and 26 ème congrès de l'AIPU
Published: 2010

6. Apport de la loi de probabilité GEV pour la modélisation des durées opératoires et d’évolution du degré d’invalidité des personnes âgées

Author: Louvain School of Management - Operations and Information, Université St Etienne - FUCaM autre, FUCaM autre - FUCaM autre, FUCAM - Sciences de gestion, Combes, Catherine, Dussauchoy, Alain, Meskens, Nadine, 5ème édition de la conférence Gestion et Ingénierie des Systèmes Hospitaliers, GISEH 10, Louvain School of Management - Operations and Information, Université St Etienne - FUCaM autre, FUCaM autre - FUCaM autre, FUCAM - Sciences de gestion, Combes, Catherine, Dussauchoy, Alain, Meskens, Nadine, and 5ème édition de la conférence Gestion et Ingénierie des Systèmes Hospitaliers, GISEH 10
Abstract: Les systèmes de santé sont confrontés à de nombreux problèmes tels que le choix des ressources, le dimensionnement de ces dernières, l’étude de nouvelles politiques de gestion et de pilotage de leur système…Ces problèmes peuvent être résolus entre autres, grâce à la modélisation par simulation à événements discrets. Ces modèles de simulation doivent être une représentation la plus fidèle du phénomène observé, d’où l’importance du choix des lois de probabilité qui modélisent au mieux le phénomène observé. Dans cet article nous présentons une loi de probabilité peu connue, mais qui permet aussi bien de modéliser des phénomènes suivant une loi normale que des phénomènes suivant une loi de Weibull. Cette loi appelée GEV (Generalized Extreme Value) est essentiellement utilisée pour l’étude des phénomènes de la théorie des valeurs extrêmes. Cependant, vu ses propriétés fort intéressantes, cette loi peut être utile dans un autre contexte que l’étude des valeurs extrêmes. Nous présentons également les principales caractéristiques de cette loi de probabilité. Nous montrons que cette loi permet d’ajuster « correctement » des durées opératoires et des durées de maintien dans un degré d’autonomie-handicap des personnes âgées résidant dans des maisons de retraite médicalisées.
Published: 2010

7. Intérêt de l’imagerie par résonance magnétique

Author: Biennale d'Onychologie (III: 25 January, 2002: St Etienne), Richert, Bertrand, Biennale d'Onychologie (III: 25 January, 2002: St Etienne), and Richert, Bertrand
Abstract: info:eu-repo/semantics/nonPublished
Published: 2002

8. Study of final height in Turner's syndrome: ethnic and genetic influences

Author: Rochiccioli (Toulouse), P, primary, David (Lyon), M, additional, Malpuech (Clermont Ferrand), G, additional, Colle (Bordeaux), M, additional, Limal (Angers), J M, additional, Battin (Bordeaux), J, additional, Mariani (Nice), R, additional, Sultan (Montpellier), C, additional, Nivelon (Dijon), J L, additional, Simonin (Marseille), G, additional, Bost (Grenoble), M, additional, Chatelain (Lyon), P, additional, Bertrand (Besancon), A M, additional, Freycon (St Etienne), R, additional, Bouquier (Limoges), J J, additional, and Pierron (Toulon), P, additional
Published: 1994
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9. La Ruche harmonieuse, 30 choeurs à quatre voix d'hommes, sans accomp.t musique de Félicien David

Author: Chaubet, Charles. Auteur du texte, St Etienne, Sylvain. Auteur du texte, Deschamps, Émile (1791-1871). Auteur du texte, St Etienne, S.. Auteur du texte, Méry, Joseph (1797-1866). Auteur du texte, Gabriel, J.. Auteur du texte, Villemain. Auteur du texte, David, Félicien (1810-1876). Compositeur, Chaubet, Charles. Auteur du texte, St Etienne, Sylvain. Auteur du texte, Deschamps, Émile (1791-1871). Auteur du texte, St Etienne, S.. Auteur du texte, Méry, Joseph (1797-1866). Auteur du texte, Gabriel, J.. Auteur du texte, Villemain. Auteur du texte, and David, Félicien (1810-1876). Compositeur

10. Complexity, algorithmic, and computational aspects of a dial-a-ride type problem

Author: Mourad Baïou, Rafael Colares, Hervé Kerivin, Laboratoire d'Informatique, de Modélisation et d'Optimisation des Systèmes (LIMOS), Ecole Nationale Supérieure des Mines de St Etienne (ENSM ST-ETIENNE)-Centre National de la Recherche Scientifique (CNRS)-Université Clermont Auvergne (UCA)-Institut national polytechnique Clermont Auvergne (INP Clermont Auvergne), Université Clermont Auvergne (UCA)-Université Clermont Auvergne (UCA), Ecole Nationale Supérieure des Mines de St Etienne (ENSM ST-ETIENNE)-Université Clermont Auvergne [2017-2020] (UCA [2017-2020])-Centre National de la Recherche Scientifique (CNRS), Department of Mathematical Sciences [Clemson], Clemson University, and COLARES, RAFAEL
Subjects: [INFO.INFO-CC]Computer Science [cs]/Computational Complexity [cs.CC], Combinatorial optimization, computational complexity, Information Systems and Management, [INFO.INFO-RO] Computer Science [cs]/Operations Research [cs.RO], General Computer Science, polyhedral study, [INFO.INFO-RO]Computer Science [cs]/Operations Research [cs.RO], Management Science and Operations Research, Industrial and Manufacturing Engineering, [MATH.MATH-CO] Mathematics [math]/Combinatorics [math.CO], Computer Science::Robotics, Modeling and Simulation, [MATH.MATH-CO]Mathematics [math]/Combinatorics [math.CO], [INFO.INFO-CC] Computer Science [cs]/Computational Complexity [cs.CC], autonomous vehicles, dial-a-ride
Abstract: In dial-a-ride systems involving autonomous vehicles circulating along a circuit, a fleet of vehicles must serve clients who request rides between stations of the circuit such that the total number of pickup and drop-off operations is minimized. In this paper, we focus on a unitary variant where each client requests a single place in the vehicles and all the clients must be served within a single tour of the circuit. Such unitary variant induces a combinatorial optimization problem for which we introduce a nontrivial special case that is polynomially solvable when the capacity of each vehicle is at most 2 but it is NP-Hard otherwise. We also study the polytope associated with the solutions to this problem. We introduce new families of valid inequalities and give necessary and sufficient conditions under which they are facet-defining. Based on these inequalities, we devise an efficient branch-and-cut algorithm that outperforms the state-of-the-art commercial solvers.
Published: 2023

11. Dynamic scheduling of patients in emergency departments

Author: Thiago Alves de Queiroz, Manuel Iori, Arthur Kramer, Yong-Hong Kuo, Università degli Studi di Modena e Reggio Emilia = University of Modena and Reggio Emilia (UNIMORE), École des Mines de Saint-Étienne (Mines Saint-Étienne MSE), Institut Mines-Télécom [Paris] (IMT), Institut Henri Fayol (FAYOL-ENSMSE), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), Département Génie mathématique et industriel (FAYOL-ENSMSE), Ecole Nationale Supérieure des Mines de St Etienne (ENSM ST-ETIENNE)-Institut Henri Fayol, Laboratoire d'Informatique, de Modélisation et d'Optimisation des Systèmes (LIMOS), Ecole Nationale Supérieure des Mines de St Etienne (ENSM ST-ETIENNE)-Centre National de la Recherche Scientifique (CNRS)-Université Clermont Auvergne (UCA)-Institut national polytechnique Clermont Auvergne (INP Clermont Auvergne), Université Clermont Auvergne (UCA)-Université Clermont Auvergne (UCA), Universidade Federal do Rio Grande do Norte [Natal] (UFRN), and The University of Hong Kong (HKU)
Subjects: [SDV.EE.SANT]Life Sciences [q-bio]/Ecology, environment/Health, Scheduling, Healthcare, Emergency department, Variable neighborhood search, Weighted tardiness, Information Systems and Management, General Computer Science, Management Science and Operations Research, Industrial and Manufacturing Engineering, [SPI]Engineering Sciences [physics], Modeling and Simulation, [SPI.GPROC]Engineering Sciences [physics]/Chemical and Process Engineering
Abstract: International audience; Emergency department overcrowding is a global issue that poses a great threat to patient health and safety. The timeliness of medical services provided to patients is crucial to emergency departments as it directly impacts the mortality and morbidity of urgent patients. However, critical resources (e.g., doctors and nurses) are typically constrained due to the limited financial budget. Thus, hospital administrators may need to investigate solutions to improve the efficiency of the emergency department. In this work, we study the dynamic problem of scheduling patients to doctors, aiming at minimizing the total weighted tardiness. We propose a simple reoptimization heuristic based on multiple queues of patients in accordance with their urgency levels, and then combine it with an effective variable neighborhood search. We also propose a scenario-based planning approach that uses sampled scenarios to anticipate future events and the variable neighborhood search to schedule patients. The methods are adapted to handle a problem variant where information on arrival time and urgency level of some patients can be received in advance by the emergency department. With a comprehensive computational study on two sets of realistic instances from Hong Kong SAR of China and Italy, we validate the performance of the proposed methods, evaluating the benefits of having more doctors and receiving early information.
Published: 2023

12. Neighbour sum distinguishing edge-weightings with local constraints

Author: Antoine Dailly, Elżbieta Sidorowicz, Instituto de Matematicas (UNAM), Universidad Nacional Autónoma de México = National Autonomous University of Mexico (UNAM), Optimisation Combinatoire (G-SCOP_OC), Laboratoire des sciences pour la conception, l'optimisation et la production (G-SCOP), Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA), Laboratoire d'Informatique, de Modélisation et d'Optimisation des Systèmes (LIMOS), Ecole Nationale Supérieure des Mines de St Etienne (ENSM ST-ETIENNE)-Centre National de la Recherche Scientifique (CNRS)-Université Clermont Auvergne (UCA)-Institut national polytechnique Clermont Auvergne (INP Clermont Auvergne), Université Clermont Auvergne (UCA)-Université Clermont Auvergne (UCA), and University of Zielona Góra
Subjects: FOS: Computer and information sciences, Discrete Mathematics (cs.DM), Applied Mathematics, [MATH.MATH-CO]Mathematics [math]/Combinatorics [math.CO], FOS: Mathematics, Mathematics - Combinatorics, Discrete Mathematics and Combinatorics, Combinatorics (math.CO), [INFO.INFO-DM]Computer Science [cs]/Discrete Mathematics [cs.DM], Computer Science - Discrete Mathematics
Abstract: A $k$-edge-weighting of $G$ is a mapping $\omega:E(G)\longrightarrow \{1,\ldots,k\}$. The edge-weighting of $G$ naturally induces a vertex-colouring $\sigma_{\omega}:V(G)\longrightarrow \mathbb{N}$ given by$\sigma_{\omega}(v)=\sum_{u\in N_G(v)}\omega(vu)$ for every $v\in V(G)$. The edge-weighting $\omega$ is neighbour sum distinguishing if it yields a proper vertex-colouring $\sigma_{\omega}$, \emph{i.e.}, $\sigma_{\omega}(u)\neq \sigma_{\omega}(v)$ for every edge $uv$ of $G$.We investigate a neighbour sum distinguishing edge-weighting with local constraints, namely, we assume that the set of edges incident to a vertex of large degree is not monochromatic. A graph is nice if it has no components isomorphic to $K_2$. We prove that every nice graph with maximum degree at most~5 admits a neighbour sum distinguishing $(\Delta(G)+2)$-edge-weighting such that all the vertices of degree at least~2 are incident with at least two edges of different weights. Furthermore, we prove that every nice graph admits a neighbour sum distinguishing $7$-edge-weighting such that all the vertices of degree at least~6 are incident with at least two edges of different weights. Finally, we show that nice bipartite graphs admit a neighbour sum distinguishing $6$-edge-weighting such that all the vertices of degree at least~2 are incident with at least two edges of different weights.
Published: 2023

13. Mechanical properties of grain boundaries

Author: McLean D., Conference on grain boundaries, St. Etienne, France, June 1975, McLean D., and Conference on grain boundaries, St. Etienne, France, June 1975
Abstract: Much experimental evidence shows that many common metals have only a small margin of safety against brittle behaviour by intergranular fracture. A reduction of the normal intergranular cohesion by approximately one third is often dangerous. This fairly critical situation is explained, and the method is given of estimating the degree of purity which will prevent the accumulation of foreign elements at grain boundaries that can cause the brittleness. Sliding at grain boundaries and plastic deformation of polycrystals are also briefly discussed., Much experimental evidence shows that many common metals have only a small margin of safety against brittle behaviour by intergranular fracture. A reduction of the normal intergranular cohesion by approximately one third is often dangerous. This fairly critical situation is explained, and the method is given of estimating the degree of purity which will prevent the accumulation of foreign elements at grain boundaries that can cause the brittleness. Sliding at grain boundaries and plastic deformation of polycrystals are also briefly discussed.
Published: 1976

14. Duo d'Agathe et d'Annette : de Freyschütz : opéra [en 3 actes] / livret de F. Kind ; trad. de Sylvain St Etienne ; musique de C. M. de Weber ; [réduction pour soprano, mezzo soprano et piano]

Author: Kind, Friedrich (1768-1843). Librettiste, Sylvain St Etienne. Traducteur, Weber, Carl Maria von (1786-1826). Compositeur, Kind, Friedrich (1768-1843). Librettiste, Sylvain St Etienne. Traducteur, and Weber, Carl Maria von (1786-1826). Compositeur
Abstract: Titre uniforme : Weber, Carl Maria von (1786-1826). Compositeur. [Der Freischütz. J 277], Collection : Ecole classique du chant... ; 20, Collection : Ecole classique du chant... ; 20

15. Mutational spectrum in a worldwide study of 29,700 families with BRCA1 or BRCA2 mutations

Author: [ 1 ] Harvard TH Chan Sch Publ Hlth, Boston, MA USA Show more [ 2 ] Chaim Sheba Med Ctr, Inst Human Genet, Susanne Levy Gertner Oncogenet Unit, IL-52621 Ramat Gan, Israel Show more [ 3 ] Tel Aviv Univ, Sackler Sch Med, Tel Aviv, Israel Show more [ 4 ] German Canc Res Ctr, Mol Genet Breast Canc, Heidelberg, Germany Show more [ 5 ] Univ Chicago, Ctr Clin Canc Genet & Global Hlth, Chicago, IL 60637 USA [ 6 ] Hong Kong Sanat & Hosp, Canc Genet Ctr, Hong Kong Hereditary Breast Canc Family Registry, Hong Kong, Hong Kong, Peoples R China Show more [ 7 ] Natl Inst Oncol, Dept Mol Genet, Budapest, Hungary Show more [ 8 ] Univ Buenos Aires, CONICET, Fac Med, INBIOMED, Buenos Aires, DF, Argentina Show more [ 9 ] CEMIC, Dept Clin Chem, Med Direct, Buenos Aires, DF, Argentina [ 10 ] Sime Darby Med Ctr, Canc Res Initiat Fdn, Subang Jaya, Malaysia Show more [ 11 ] Odense Univ Hosp, Dept Clin Genet, Odense, Denmark Show more [ 12 ] City Hope Canc Ctr, Div Clin Canc Genom, Duarte, CA USA [ 13 ] Hong Kong Sanat & Hosp, Dept Pathol, Div Mol Pathol, Happy Valley, Hong Kong, Peoples R China [ 14 ] Dept Lab Med & Pathol, Rochester, MN USA Show more [ 15 ] Univ Utah, Sch Med, Dept Dermatol, Salt Lake City, UT USA Show more [ 16 ] Barretos Canc Hosp, Mol Oncol Res Ctr, Sao Paulo, Brazil Show more [ 17 ] Seoul Natl Univ, Coll Med, Dept Prevent Med, Seoul, South Korea Show more [ 18 ] Seoul Natl Univ, Grad Sch, Dept Biomed Sci, Seoul, South Korea Show more [ 19 ] Seoul Natl Univ, Canc Res Ctr, Seoul, South Korea Show more [ 20 ] Pontificia Univ Javeriana, Inst Human Genet, Bogota, Colombia Show more [ 21 ] Univ Pretoria, Dept Genet, Canc Genet Lab, Pretoria, South Africa Show more [ 22 ] Univ Cambridge, Dept Publ Hlth & Primary Care, Ctr Canc Genet Epidemiol, Cambridge, England Show more [ 23 ] QIMR Berghofer Med Res Inst, Genet & Computat Biol Dept, Brisbane, Qld, Australia [ 24 ] Acad Med Ctr, Dept Clin Genet, Amsterdam, Netherlands [ 25 ] City Hope Clin Canc Genom Community Res Network, D, Harvard TH Chan School of Public Health and Dana Farber Cancer Institute; Boston USA, The Susanne Levy Gertner Oncogenetics Unit; Institute of Human Genetics; Chaim Sheba Medical Center, Ramat Gan 52621, and the Sackler School of Medicine; Tel-Aviv University; Tel-Aviv Israel, Molecular Genetics of Breast Cancer; German Cancer Research Center (DKFZ); Heidelberg Germany, Center for Clinical Cancer Genetics and Global Health; University of Chicago; Chicago USA, The Hong Kong Hereditary Breast Cancer Family Registry; Cancer Genetics Center; Hong Kong Sanatorium and Hospital; Hong Kong China, Department of Molecular Genetics; National Institute of Oncology; Budapest Hungary, INBIOMED; Faculty of Medicine, University of Buenos Aires/CONICET and CEMIC, Department of Clinical Chemistry; Medical Direction; Buenos Aires Argentina, Cancer Research Initiatives Foundation; Sime Darby Medical Centre; Subang Jaya Malaysia, Department of Clinical Genetics; Odense University Hospital; Odense Denmark, Center for Familial Breast and Ovarian Cancer, Center for Integrated Oncology (CIO), Medical Faculty; University Hospital Cologne; Cologne Germany, Clinical Genetics Services; Dept. of Medicine; Memorial Sloan-Kettering Cancer Center; New York USA, Division of Gynecologic Oncology; North Shore University Health System; University of Chicago; Evanston USA, All Wales Medical Genetics Services; University Hospital of Wales; Cardiff UK, Department of Gynecology; Vilnius University Hospital Santariskiu Clinics; Centre of Woman's Health and pathology; Vilnius Lithuania, Center for Genomic Medicine; Rigshospitalet; University of Copenhagen; Copenhagen Denmark, Clinical Cancer Genetics Program; Division of Human Genetics; Department of Internal Medicine; The Comprehensive Cancer Center; The Ohio State University; Columbus USA, Cancer Genetics Laboratory, Department of Genetics; University of Pretoria; South Africa, Department of Genetics and Pathology; Pomeranian Medical University; Szczecin Poland, Department of Medicine, Abramson Cancer Center; Perelman School of Medicine at the University of Pennsylvania; Philadelphia USA, Department of Internal Medicine; Division of Oncology; University of Kansas Medical Center; Westwood USA, North East Thames Regional Genetics Service; Great Ormond Street Hospital for Children NHS Trust; London UK, Genomics Center; Centre Hospitalier Universitaire de Québec Research Center and Laval University; Quebec City Canada, Dept of OB/GYN and Comprehensive Cancer Center; Medical University of Vienna; Vienna Austria, Department of Clinical Genetics; Aarhus University Hospital; Aarhus N Denmark, Division of Clinical Cancer Genomics; City of Hope Cancer Center; California USA, Medical Genetics Unit; University of London; St George's UK, Département Oncologie Génétique; Prévention et Dépistage; Institut Paoli-Calmettes; Marseille Medical School-AM University; Marseille France, Department of Breast Medical Oncology and Clinical Cancer Genetics Program; University Of Texas MD Anderson Cancer Center; Houston USA, Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care; University of Cambridge; Cambridge UK, Department of Population Sciences; Beckman Research Institute of City of Hope; Duarte USA, Institute of Cell and Molecular Pathology; Hannover Medical School; Hannover Germany, Institute of Human Genetics; University Hospital Heidelberg; Heidelberg Germany, National Human Genome Research Institute; National Institutes of Health; Bethesda USA, Dept of OB/GYN, Comprehensive Cancer Center; Medical University of Vienna; Vienna Austria, Department of Genetics; Portuguese Oncology Institute of Porto (IPO Porto); Porto Portugal, Department of Epidemiology; Columbia University; New York USA, Genetic Counseling Unit; Hereditary Cancer Program; IDIBELL (Bellvitge Biomedical Research Institute); Catalan Institute of Oncology, CIBERONC; Gran Via de l'Hospitalet; Barcelona Spain, Department of Health Sciences Research; Mayo Clinic; Rochester USA, Genetics and Computational Biology Department; QIMR Berghofer Medical Research Institute; Brisbane Australia, Department of Medicine; Magee-Womens Hospital; University of Pittsburgh School of Medicine; Pittsburgh USA, Program in Cancer Genetics; Departments of Human Genetics and Oncology; McGill University; Montreal Canada, Immunology and Molecular Oncology Unit; Veneto Institute of Oncology IOV - IRCCS; Padua Italy, Division of Human Genetics; Departments of Internal Medicine and Cancer Biology and Genetics; Comprehensive Cancer Center; The Ohio State University; Columbus USA, Clinical Genetics Research Laboratory, Dept. of Medicine; Memorial Sloan-Kettering Cancer Center; New York USA, Parkville Familial Cancer Centre; Royal Melbourne Hospital; Melbourne Australia, Department of Medical Oncology; Beth Israel Deaconess Medical Center; Massachusetts USA, Department of Clinical Genetics; Leiden University Medical Center; Leiden The Netherlands, Department of Genetics; University Medical Center; Groningen University; Groningen The Netherlands, Family Cancer Clinic; Netherlands Cancer Institute; Amsterdam The Netherlands, Department of Medical Genetics; University Medical Center; Utrecht The Netherlands, Center for Medical Genetics; Ghent University; Gent Belgium, Unit of Hereditary Cancer; Department of Epidemiology, Prevention and Special Functions; IRCCS (Istituto Di Ricovero e Cura a Carattere Scientifico) AOU San Martino - IST Istituto Nazionale per la Ricerca sul Cancro; Genoa Italy, Institute of Human Genetics; Campus Virchov Klinikum; Berlin Germany, Fundación Pública Galega de Medicina Xenómica-SERGAS, Grupo de Medicina Xenómica-USC, CIBERER, IDIS, Santiago de Compostela; Spain, Departamento de Investigacion y de Tumores Mamarios del; Instituto Nacional de Cancerologia; Mexico City Mexico, Department of Oncology; Karolinska University Hospital; Stockholm Sweden, Institute of Genetic Medicine; Centre for Life; Newcastle Upon Tyne Hospitals NHS Trust; Newcastle upon Tyne UK, Oxford Regional Genetics Service; Churchill Hospital; Oxford UK, Department of Gynaecology and Obstetrics; University Hospital; Ulm Germany, Department of Clinical Genetics; Academic Medical Center; Amsterdam The Netherlands, Institute of Human Genetics; Regensburg University; Regensburg Germany, Molecular Diagnostics Laboratory, INRASTES (Institute of Nuclear and Radiological Sciences and Technology); National Centre for Scientific Research “Demokritos”; Athens Greece, Unit of Medical Genetics, Department of Medical Oncology and Hematology; Fondazione IRCCS (Istituto Di Ricovero e Cura a Carattere Scientifico) Instituto Nazionale Tumori (INT); Milan Italy, Institute of Oncology; Rivka Ziv Medical Center; Zefat Israel, Magee-Womens Hospital; University of Pittsburgh School of Medicine; Pittsburgh USA, Institute of Human Genetics; University Leipzig; Leipzig Germany, Center for Medical Genetics; North Shore University Health System; Evanston USA, Medical Director, Center for Medical Genetics, NorthShore University HealthSystem, Clinical Assistant Professor of Medicine; University of Chicago Pritzker School of Medicine; Evanston USA, City of Hope Clinical Cancer Genomics Community Research Network; Duarte USA, Yorkshire Regional Genetics Service; Chapel Allerton Hospital; Leeds UK, Department of Clinical Genetics; Helsinki University Hospital; Helsinki Finland, Hereditary Cancer Clinic; Prince of Wales Hospital; Randwick Australia, Lunenfeld-Tanenbaum Research Institute; Toronto Canada, Laboratory of Cell Biology, Department of Pathology, hus 9, Landspitali-LSH v/Hringbraut, 101 Reykjavik, Iceland and BMC (Biomedical Centre), Faculty of Medicine; University of Iceland; Reykjavik Iceland, Department of Gynaecology & Oncology; Medical University of Vienna; Austria, Department of Medical Oncology; Vall d'Hebron University Hospital; Barcelona Spain, Division of Cancer Prevention and Genetics; Istituto Europeo di Oncologia (IEO); Milan Italy, Department of Gynaecology and Obstetrics; University Hospital Düsseldorf, Heinrich-Heine University; Düsseldorf Germany, Human Genetics Group and Genotyping Unit (CEGEN), Human Cancer Genetics Programme; Spanish National Cancer Research Centre (CNIO); Madrid Spain, The Institute of Oncology; Chaim Sheba Medical Center; Ramat Gan Israel, UCSF Cancer Genetics and Prevention Program; San Francisco USA, Department of Clinical Genetics; Maastricht University Medical Center; Maastricht The Netherlands, Unité de Prévention et d'Epidémiologie Génétique; Centre Léon Bérard, 28 rue Laënnec; Lyon France, N.N. Petrov Institute of Oncology; St. Petersburg Russia, Department of Clinical Genetics; Royal Devon & Exeter Hospital; Exeter UK, Service de Génétique; Institut Curie, 26 rue d'Ulm; Paris France, Department of Medicine; Huntsman Cancer Institute; Salt Lake City USA, Molecular Oncology Laboratory; Hospital Clinico San Carlos; Instituto de Investigación Sanitaria San Carlos (IdISSC); Centro Investigación Biomédica en Red de Cáncer (CIBERONC); Madrid Spain, Institute of Human Genetics; University Hospital of Schleswig-Holstein; Kiel Germany, Section of Molecular Genetics, Dept. of Laboratory Medicine; University Hospital of Pisa; Pisa Italy, Research Division; Peter MacCallum Cancer Centre; Melbourne Australia, CRCHU de Quebec-oncologie, Centre des maladies du sein Deschênes-Fabia; Hôpital du Saint-Sacrement; Sainte-Foy Canada, Lombardi Comprehensive Cancer Center; Georgetown University; Washington USA, Departments of Pediatrics and Medicine; Columbia University; New York USA, Department of Clinical Genetics, Family Cancer Clinic; Erasmus University Medical Center; Rotterdam The Netherlands, Sheffield Clinical Genetics Service; Sheffield Children's Hospital; Sheffield UK, Department of Clinical Genetics; South Glasgow University Hospitals; Glasgow UK, Unité d'oncogénétique; ICO-Centre René Gauducheau; Saint Herblain France, Oncogenetics Group, Vall d'Hebron Institute of Oncology (VHIO), Clinical and Molecular Genetics Area; Vall d'Hebron University Hospital; Barcelona Spain, Department of Gynaecology and Obstetrics; Ludwig-Maximilian University; Munich Germany, Cáncer Hereditario, Instituto de Biología y Genética Molecular, IBGM; Universidad de Valladolid; Valladolid Spain, Institute of Human Genetics; University of Münster; Münster Germany, Nottingham Clinical Genetics Service; Nottingham University Hospitals NHS Trust; Nottingham UK, Oncogenetics Team; The Institute of Cancer Research and Royal Marsden NHS Foundation Trust; London UK, Department of Clinical Genetics; Lund University Hospital; Lund Sweden, Clinical Genetics; Guy's and St. Thomas’ NHS Foundation Trust; London UK, Department of Oncology, Rigshospitalet; Copenhagen University Hospital; Copenhagen Denmark, Institute for Medical Informatics, Statistics and Epidemiology; University of Leipzig; Leipzig Germany, Department of Gynaecology and Obstetrics, Division of Tumor Genetics, Klinikum rechts der Isar; Technical University; Munich Germany, Genomic Medicine, Manchester Academic Health Sciences Centre, Division of Evolution and Genomic Sciences; University of Manchester, Central Manchester University Hospitals NHS Foundation Trust; Manchester UK, Centre de Lutte Contre le Cancer Georges François Leclerc, France and Genomic and Immunotherapy Medical Institute; Dijon University Hospital; Dijon France, Molecular Diagnostic Unit, Hereditary Cancer Program, ICO-IDIBELL (Catalan Institute of Oncology-Bellvitge Biomedical Research Institute); Barcelona Spain, Laboratoire de Génétique Chromosomique; Hôtel Dieu Centre Hospitalier; Chambéry France, Department of Cancer Epidemiology and Genetics; Masaryk Memorial Cancer Institute; Brno Czech Republic, Columbus Cancer Council, Ohio State University; Columbus USA, Genetic Counseling Unit, Hereditary Cancer Program, IDIBGI (Institut d'Investigació Biomèdica de Girona); Catalan Institute of Oncology; Girona Spain, Oncogenetics Department; Barretos Cancer Hospital; Barretos Brazil, UCLA Schools of Medicine and Public Health, Division of Cancer Prevention & Control Research; Jonsson Comprehensive Cancer Center; Los Angeles USA, Cancer Risk and Prevention Clinic; Dana-Farber Cancer Institute; Boston USA, Centre of Familial Breast and Ovarian Cancer, Department of Medical Genetics, Institute of Human Genetics; University of Würzburg, Germany; Würzburg, Department of Clinical Genetics; Copenhagen Denmark, Service Régional Oncogénétique Poitou-Charentes; Centre Hospitalier; Niort France, Department of Molecular Medicine; University La Sapienza, and Istituto Pasteur - Fondazione Cenci-Bolognetti; Rome Italy, Bâtiment Cheney D; Centre Léon Bérard; Lyon France, Ontario Cancer Genetics Network: Lunenfeld-Tanenbaum Research Institute; Mount Sinai Hospital; Toronto Canada, Department of Pathology and Laboratory Medicine; University of Kansas Medical Center; Kansas City USA, Clinical Genetics Branch, DCEG, NCI; NIH; Bethesda USA, Parkville Familial Cancer Centre; Peter MacCallum Cancer Centre; Melbourne Australia, Hematology, oncology and transfusion medicine center, Dept. of Molecular and Regenerative Medicine; Vilnius University Hospital Santariskiu Clinics; Vilnius Lithuania, Department of Epidemiology, Cancer Prevention Institute of California; Fremont USA, Women's Cancer Program at the Samuel Oschin Comprehensive Cancer Institute; Cedars-Sinai Medical Center; Los Angeles USA, Division of Molecular Pathology; Department of Pathology; Hong Kong Sanatorium & Hospital; Happy Valley Hong Kong, Department of Gynecology and Obstetrics; Medical Faculty and University Hospital Carl Gustav Carus; Dresden Germany, Research Department, Peter MacCallum Cancer Centre, Melbourne, Victoria; Australia and The Sir Peter MacCallum Department of Oncology University of Melbourne; Parkville Australia, Department of Surgery; Daerim St. Mary's Hospital; Seoul Korea, The Gyneco-Oncology Department; Chaim Sheba Medical Center; Ramat Gan Israel, Servicio de Genética-CIBERER U705; Hospital de la Santa Creu i Sant Pau; Barcelona Spain, The Feinstein Institute for Medical Research; Manhasset USA, Department of Laboratory Medicine and Pathology; and Health Sciences Research; Rochester USA, Department of Surgery; Soonchunhyang University and Seoul Hospital; Seoul Korea, Inserm U900, Institut Curie; PSL Research University; Paris France, Department of Oncology Radiumhemmet and Institution of Oncology and Patology; Karolinska University Hospital and Karolinska Institutet; Solna Sweden, Department of Health Sciences Research; Mayo Clinic; Scottsdale USA, Oncogénétique; Institut Bergonié; Bordeaux France, Clinical Genetics Branch, DCEG, NCI, NIH; Bethesda USA, Department of Gynecological Oncology and Clinical Cancer Genetics Program; University Of Texas MD Anderson Cancer Center; Houston USA, Department of Dermatology; University of Utah School of Medicine; Salt Lake City USA, Centre Antoine Lacassagne; Nice France, Laboratorio de Genética Molecular, Servicio de Genética; Hospital Universitario Cruces, BioCruces Health Research Institute; Barakaldo Spain, Department of Surgery; National Institute of Oncology; Budapest Hungary, Department of Clinical Genetics; VU University Medical Center; Amsterdam The Netherlands, Department of Human Genetics; Radboud University Medical Center; Nijmegen The Netherlands, Vilnius university Santariskiu hospital; National Center of Pathology; Vilnius Lithuania, NRG Oncology; Statistics and Data Management Center; Roswell Park Cancer Institute; Buffalo USA, Department of Cancer Prevention and Control; Roswell Park Cancer Institute; Buffalo USA, Department of Laboratory Medicine and Pathobiology; University of Toronto; Toronto Canada, Department of Obstetrics and Gynecology; University of Helsinki and Helsinki University Hospital; HUS Finland, Cancer Genetics Service; Division of Medical Oncology; National Cancer Centre Singapore; Bukit Merah Singapore, Institute of Medical Genetics and Applied Genomics; University of Tuebingen; Tuebingen Germany, Molecular Oncology Research Center; Barretos Cancer Hospital; São Paulo Brazil, Cancer Genetics and Prevention Program; University of California San Francisco; San Francisco USA, Clinical Genetics Research Laboratory; Dept. of Medicine; Cancer Biology and Genetics; Memorial Sloan-Kettering Cancer Center; New York USA, Department of Clinical Genetics; Sahlgrenska University Hospital; Gothenburg Sweden, West Midlands Regional Genetics Service; Birmingham Women's Hospital Healthcare NHS Trust; Edgbaston UK, Human Genetics Group; Human Cancer Genetics Programme; Spanish National Cancer Research Centre (CNIO); Biomedical Network on Rare Diseases (CIBERER); Madrid Spain, Unit of Medical Genetics; Department of Biomedical; Experimental and Clinical Sciences; University of Florence; Florence Italy, Department of Medical Sciences; University of Turin; Turin Italy, Section of Molecular Diagnostics; Department of Biochemistry; Aalborg University Hospital; Aalborg Denmark, Department of Preventive Medicine; Seoul National University College of Medicine; Seoul Korea, IFOM; The FIRC (Italian Foundation for Cancer Research) Institute of Molecular Oncology; Milan Italy, Service de Génétique Clinique Chromosomique et Moléculaire; Hôpital Nord; St Etienne France, Unité d'Oncogénétique; CHU Arnaud de Villeneuve; Montpellier France, Unit of Molecular Bases of Genetic Risk and Genetic Testing; Department of Research; Fondazione IRCCS (Istituto Di Ricovero e Cura a Carattere Scientifico), Istituto Nazionale Tumori (INT); Milan Italy, School of Women's and Children's Health; UNSW; Sydney Australia, Department of Clinical Genetics; Karolinska University Hospital; Stockholm Sweden, Rebbeck, Timothy R., Friebel, Tara M., Friedman, Eitan, Hamann, Ute, Huo, Dezheng, Kwong, Ava, Olah, Edith, Olopade, Olufunmilayo I., Solano, Angela R., Teo, Soo-Hwang, Thomassen, Mads, Rashid, Muhammad Usman, Rhiem, Kerstin, Robson, Mark, Rodriguez, Gustavo C., Rogers, Mark T., Rudaitis, Vilius, Schmidt, Ane Y., Schmutzler, Rita Katharina, Senter, Leigha, van Rensburg, Elizabeth J., Gronwald, Jacek, Shah, Payal D., Sharma, Priyanka, Side, Lucy E., Simard, Jacques, Singer, Christian F., Skytte, Anne-Bine, Slavin, Thomas P., Snape, Katie, Sobol, Hagay, Southey, Melissa, Gutierrez-Barrera, Angelica, McGuffog, Lesley, Steele, Linda, Steinemann, Doris, Sukiennicki, Grzegorz, Sutter, Christian, Szabo, Csilla I., Tan, Yen Y., Teixeira, Manuel R., Terry, Mary Beth, Teulé, Alex, Hahnen, Eric, Thomas, Abigail, Parsons, Michael T., Thull, Darcy L., Tischkowitz, Marc, Tognazzo, Silvia, Toland, Amanda Ewart, Topka, Sabine, Trainer, Alison H, Tung, Nadine, van Asperen, Christi J., Hauke, Jan, van der Hout, Annemieke H., van der Kolk, Lizet E., Leslie, Goska, van der Luijt, Rob B., Van Heetvelde, Mattias, Varesco, Liliana, Varon-Mateeva, Raymonda, Vega, Ana, Villarreal-Garza, Cynthia, von Wachenfeldt, Anna, Henderson, Alex, Walker, Lisa, Wang-Gohrke, Shan, Wappenschmidt, Barbara, Aalfs, Cora M., Weber, Bernhard H. F., Yannoukakos, Drakoulis, Yoon, Sook-Yee, Zanzottera, Cristina, Zidan, Jamal, Zorn, Kristin K., Hentschel, Julia, Hutten Selkirk, Christina G., Hulick, Peter J., Chenevix-Trench, Georgia, Spurdle, Amanda B., Abugattas, Julio, Antoniou, Antonis C., Nathanson, Katherine L., Adlard, Julian, Agata, Simona, Aittomäki, Kristiina, Hogervorst, Frans B.L., Andrews, Lesley, Andrulis, Irene L., Arason, Adalgeir, Arnold, Norbert, Arun, Banu K., Asseryanis, Ella, Auerbach, Leo, Azzollini, Jacopo, Balmaña, Judith, Barile, Monica, Honisch, Ellen, Barkardottir, Rosa B., Barrowdale, Daniel, Benitez, Javier, Berger, Andreas, Berger, Raanan, Blanco, Amie M., Blazer, Kathleen R., Blok, Marinus J., Bonadona, Valérie, Bonanni, Bernardo, Imyanitov, Evgeny N., Bradbury, Angela R., Brewer, Carole, Buecher, Bruno, Buys, Saundra S., Caldes, Trinidad, Caliebe, Almuth, Caligo, Maria A., Campbell, Ian, Caputo, Sandrine M., Chiquette, Jocelyne, Isaacs, Claudine, Chung, Wendy K., Claes, Kathleen B.M., Collée, J. Margriet, Cook, Jackie, Davidson, Rosemarie, de la Hoya, Miguel, De Leeneer, Kim, de Pauw, Antoine, Delnatte, Capucine, Diez, Orland, Weitzel, Jeffrey N., Ding, Yuan Chun, Ditsch, Nina, Domchek, Susan M., Dorfling, Cecilia M., Velazquez, Carolina, Dworniczak, Bernd, Eason, Jacqueline, Easton, Douglas F., Eeles, Ros, Ehrencrona, Hans, Izatt, Louise, Ejlertsen, Bent, Engel, Christoph, Engert, Stefanie, Evans, D. Gareth, Faivre, Laurence, Feliubadaló, Lidia, Ferrer, Sandra Fert, Foretova, Lenka, Fowler, Jeffrey, Frost, Debra, Izquierdo, Angel, Galvão, Henrique C. R., Ganz, Patricia A., Garber, Judy, Gauthier-Villars, Marion, Gehrig, Andrea, Gerdes, Anne-Marie, Gesta, Paul, Giannini, Giuseppe, Giraud, Sophie, Glendon, Gord, Jakubowska, Anna, Godwin, Andrew K., Greene, Mark H., James, Paul, Janavicius, Ramunas, Jensen, Uffe Birk, John, Esther M., Vijai, Joseph, Kaczmarek, Katarzyna, Karlan, Beth Y., Chan, TL, Kast, Karin, Investigators, KConFab, Kim, Sung-Won, Konstantopoulou, Irene, Korach, Jacob, Laitman, Yael, Lasa, Adriana, Lasset, Christine, Lázaro, Conxi, Lee, Annette, Couch, Fergus J., Lee, Min Hyuk, Lester, Jenny, Lesueur, Fabienne, Liljegren, Annelie, Lindor, Noralane M., Longy, Michel, Loud, Jennifer T., Lu, Karen H., Lubinski, Jan, Machackova, Eva, Goldgar, David E., Manoukian, Siranoush, Mari, Véronique, Martínez-Bouzas, Cristina, Matrai, Zoltan, Mebirouk, Noura, Meijers-Heijboer, Hanne E.J., Meindl, Alfons, Mensenkamp, Arjen R., Mickys, Ugnius, Miller, Austin, Kruse, Torben A., Montagna, Marco, Moysich, Kirsten B., Mulligan, Anna Marie, Musinsky, Jacob, Neuhausen, Susan L., Nevanlinna, Heli, Ngeow, Joanne, Nguyen, Huu Phuc, Niederacher, Dieter, Nielsen, Henriette Roed, Palmero, Edenir Inêz, Nielsen, Finn Cilius, Nussbaum, Robert L., Offit, Kenneth, Öfverholm, Anna, Ong, Kai-ren, Osorio, Ana, Papi, Laura, Papp, Janos, Pasini, Barbara, Pedersen, Inge Sokilde, Park, Sue Kyung, Peixoto, Ana, Peruga, Nina, Peterlongo, Paolo, Pohl, Esther, Pradhan, Nisha, Prajzendanc, Karolina, Prieur, Fabienne, Pujol, Pascal, Radice, Paolo, Ramus, Susan J., Torres, Diana, Rantala, Johanna, [ 1 ] Harvard TH Chan Sch Publ Hlth, Boston, MA USA Show more [ 2 ] Chaim Sheba Med Ctr, Inst Human Genet, Susanne Levy Gertner Oncogenet Unit, IL-52621 Ramat Gan, Israel Show more [ 3 ] Tel Aviv Univ, Sackler Sch Med, Tel Aviv, Israel Show more [ 4 ] German Canc Res Ctr, Mol Genet Breast Canc, Heidelberg, Germany Show more [ 5 ] Univ Chicago, Ctr Clin Canc Genet & Global Hlth, Chicago, IL 60637 USA [ 6 ] Hong Kong Sanat & Hosp, Canc Genet Ctr, Hong Kong Hereditary Breast Canc Family Registry, Hong Kong, Hong Kong, Peoples R China Show more [ 7 ] Natl Inst Oncol, Dept Mol Genet, Budapest, Hungary Show more [ 8 ] Univ Buenos Aires, CONICET, Fac Med, INBIOMED, Buenos Aires, DF, Argentina Show more [ 9 ] CEMIC, Dept Clin Chem, Med Direct, Buenos Aires, DF, Argentina [ 10 ] Sime Darby Med Ctr, Canc Res Initiat Fdn, Subang Jaya, Malaysia Show more [ 11 ] Odense Univ Hosp, Dept Clin Genet, Odense, Denmark Show more [ 12 ] City Hope Canc Ctr, Div Clin Canc Genom, Duarte, CA USA [ 13 ] Hong Kong Sanat & Hosp, Dept Pathol, Div Mol Pathol, Happy Valley, Hong Kong, Peoples R China [ 14 ] Dept Lab Med & Pathol, Rochester, MN USA Show more [ 15 ] Univ Utah, Sch Med, Dept Dermatol, Salt Lake City, UT USA Show more [ 16 ] Barretos Canc Hosp, Mol Oncol Res Ctr, Sao Paulo, Brazil Show more [ 17 ] Seoul Natl Univ, Coll Med, Dept Prevent Med, Seoul, South Korea Show more [ 18 ] Seoul Natl Univ, Grad Sch, Dept Biomed Sci, Seoul, South Korea Show more [ 19 ] Seoul Natl Univ, Canc Res Ctr, Seoul, South Korea Show more [ 20 ] Pontificia Univ Javeriana, Inst Human Genet, Bogota, Colombia Show more [ 21 ] Univ Pretoria, Dept Genet, Canc Genet Lab, Pretoria, South Africa Show more [ 22 ] Univ Cambridge, Dept Publ Hlth & Primary Care, Ctr Canc Genet Epidemiol, Cambridge, England Show more [ 23 ] QIMR Berghofer Med Res Inst, Genet & Computat Biol Dept, Brisbane, Qld, Australia [ 24 ] Acad Med Ctr, Dept Clin Genet, Amsterdam, Netherlands [ 25 ] City Hope Clin Canc Genom Community Res Network, D, Harvard TH Chan School of Public Health and Dana Farber Cancer Institute; Boston USA, The Susanne Levy Gertner Oncogenetics Unit; Institute of Human Genetics; Chaim Sheba Medical Center, Ramat Gan 52621, and the Sackler School of Medicine; Tel-Aviv University; Tel-Aviv Israel, Molecular Genetics of Breast Cancer; German Cancer Research Center (DKFZ); Heidelberg Germany, Center for Clinical Cancer Genetics and Global Health; University of Chicago; Chicago USA, The Hong Kong Hereditary Breast Cancer Family Registry; Cancer Genetics Center; Hong Kong Sanatorium and Hospital; Hong Kong China, Department of Molecular Genetics; National Institute of Oncology; Budapest Hungary, INBIOMED; Faculty of Medicine, University of Buenos Aires/CONICET and CEMIC, Department of Clinical Chemistry; Medical Direction; Buenos Aires Argentina, Cancer Research Initiatives Foundation; Sime Darby Medical Centre; Subang Jaya Malaysia, Department of Clinical Genetics; Odense University Hospital; Odense Denmark, Center for Familial Breast and Ovarian Cancer, Center for Integrated Oncology (CIO), Medical Faculty; University Hospital Cologne; Cologne Germany, Clinical Genetics Services; Dept. of Medicine; Memorial Sloan-Kettering Cancer Center; New York USA, Division of Gynecologic Oncology; North Shore University Health System; University of Chicago; Evanston USA, All Wales Medical Genetics Services; University Hospital of Wales; Cardiff UK, Department of Gynecology; Vilnius University Hospital Santariskiu Clinics; Centre of Woman's Health and pathology; Vilnius Lithuania, Center for Genomic Medicine; Rigshospitalet; University of Copenhagen; Copenhagen Denmark, Clinical Cancer Genetics Program; Division of Human Genetics; Department of Internal Medicine; The Comprehensive Cancer Center; The Ohio State University; Columbus USA, Cancer Genetics Laboratory, Department of Genetics; University of Pretoria; South Africa, Department of Genetics and Pathology; Pomeranian Medical University; Szczecin Poland, Department of Medicine, Abramson Cancer Center; Perelman School of Medicine at the University of Pennsylvania; Philadelphia USA, Department of Internal Medicine; Division of Oncology; University of Kansas Medical Center; Westwood USA, North East Thames Regional Genetics Service; Great Ormond Street Hospital for Children NHS Trust; London UK, Genomics Center; Centre Hospitalier Universitaire de Québec Research Center and Laval University; Quebec City Canada, Dept of OB/GYN and Comprehensive Cancer Center; Medical University of Vienna; Vienna Austria, Department of Clinical Genetics; Aarhus University Hospital; Aarhus N Denmark, Division of Clinical Cancer Genomics; City of Hope Cancer Center; California USA, Medical Genetics Unit; University of London; St George's UK, Département Oncologie Génétique; Prévention et Dépistage; Institut Paoli-Calmettes; Marseille Medical School-AM University; Marseille France, Department of Breast Medical Oncology and Clinical Cancer Genetics Program; University Of Texas MD Anderson Cancer Center; Houston USA, Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care; University of Cambridge; Cambridge UK, Department of Population Sciences; Beckman Research Institute of City of Hope; Duarte USA, Institute of Cell and Molecular Pathology; Hannover Medical School; Hannover Germany, Institute of Human Genetics; University Hospital Heidelberg; Heidelberg Germany, National Human Genome Research Institute; National Institutes of Health; Bethesda USA, Dept of OB/GYN, Comprehensive Cancer Center; Medical University of Vienna; Vienna Austria, Department of Genetics; Portuguese Oncology Institute of Porto (IPO Porto); Porto Portugal, Department of Epidemiology; Columbia University; New York USA, Genetic Counseling Unit; Hereditary Cancer Program; IDIBELL (Bellvitge Biomedical Research Institute); Catalan Institute of Oncology, CIBERONC; Gran Via de l'Hospitalet; Barcelona Spain, Department of Health Sciences Research; Mayo Clinic; Rochester USA, Genetics and Computational Biology Department; QIMR Berghofer Medical Research Institute; Brisbane Australia, Department of Medicine; Magee-Womens Hospital; University of Pittsburgh School of Medicine; Pittsburgh USA, Program in Cancer Genetics; Departments of Human Genetics and Oncology; McGill University; Montreal Canada, Immunology and Molecular Oncology Unit; Veneto Institute of Oncology IOV - IRCCS; Padua Italy, Division of Human Genetics; Departments of Internal Medicine and Cancer Biology and Genetics; Comprehensive Cancer Center; The Ohio State University; Columbus USA, Clinical Genetics Research Laboratory, Dept. of Medicine; Memorial Sloan-Kettering Cancer Center; New York USA, Parkville Familial Cancer Centre; Royal Melbourne Hospital; Melbourne Australia, Department of Medical Oncology; Beth Israel Deaconess Medical Center; Massachusetts USA, Department of Clinical Genetics; Leiden University Medical Center; Leiden The Netherlands, Department of Genetics; University Medical Center; Groningen University; Groningen The Netherlands, Family Cancer Clinic; Netherlands Cancer Institute; Amsterdam The Netherlands, Department of Medical Genetics; University Medical Center; Utrecht The Netherlands, Center for Medical Genetics; Ghent University; Gent Belgium, Unit of Hereditary Cancer; Department of Epidemiology, Prevention and Special Functions; IRCCS (Istituto Di Ricovero e Cura a Carattere Scientifico) AOU San Martino - IST Istituto Nazionale per la Ricerca sul Cancro; Genoa Italy, Institute of Human Genetics; Campus Virchov Klinikum; Berlin Germany, Fundación Pública Galega de Medicina Xenómica-SERGAS, Grupo de Medicina Xenómica-USC, CIBERER, IDIS, Santiago de Compostela; Spain, Departamento de Investigacion y de Tumores Mamarios del; Instituto Nacional de Cancerologia; Mexico City Mexico, Department of Oncology; Karolinska University Hospital; Stockholm Sweden, Institute of Genetic Medicine; Centre for Life; Newcastle Upon Tyne Hospitals NHS Trust; Newcastle upon Tyne UK, Oxford Regional Genetics Service; Churchill Hospital; Oxford UK, Department of Gynaecology and Obstetrics; University Hospital; Ulm Germany, Department of Clinical Genetics; Academic Medical Center; Amsterdam The Netherlands, Institute of Human Genetics; Regensburg University; Regensburg Germany, Molecular Diagnostics Laboratory, INRASTES (Institute of Nuclear and Radiological Sciences and Technology); National Centre for Scientific Research “Demokritos”; Athens Greece, Unit of Medical Genetics, Department of Medical Oncology and Hematology; Fondazione IRCCS (Istituto Di Ricovero e Cura a Carattere Scientifico) Instituto Nazionale Tumori (INT); Milan Italy, Institute of Oncology; Rivka Ziv Medical Center; Zefat Israel, Magee-Womens Hospital; University of Pittsburgh School of Medicine; Pittsburgh USA, Institute of Human Genetics; University Leipzig; Leipzig Germany, Center for Medical Genetics; North Shore University Health System; Evanston USA, Medical Director, Center for Medical Genetics, NorthShore University HealthSystem, Clinical Assistant Professor of Medicine; University of Chicago Pritzker School of Medicine; Evanston USA, City of Hope Clinical Cancer Genomics Community Research Network; Duarte USA, Yorkshire Regional Genetics Service; Chapel Allerton Hospital; Leeds UK, Department of Clinical Genetics; Helsinki University Hospital; Helsinki Finland, Hereditary Cancer Clinic; Prince of Wales Hospital; Randwick Australia, Lunenfeld-Tanenbaum Research Institute; Toronto Canada, Laboratory of Cell Biology, Department of Pathology, hus 9, Landspitali-LSH v/Hringbraut, 101 Reykjavik, Iceland and BMC (Biomedical Centre), Faculty of Medicine; University of Iceland; Reykjavik Iceland, Department of Gynaecology & Oncology; Medical University of Vienna; Austria, Department of Medical Oncology; Vall d'Hebron University Hospital; Barcelona Spain, Division of Cancer Prevention and Genetics; Istituto Europeo di Oncologia (IEO); Milan Italy, Department of Gynaecology and Obstetrics; University Hospital Düsseldorf, Heinrich-Heine University; Düsseldorf Germany, Human Genetics Group and Genotyping Unit (CEGEN), Human Cancer Genetics Programme; Spanish National Cancer Research Centre (CNIO); Madrid Spain, The Institute of Oncology; Chaim Sheba Medical Center; Ramat Gan Israel, UCSF Cancer Genetics and Prevention Program; San Francisco USA, Department of Clinical Genetics; Maastricht University Medical Center; Maastricht The Netherlands, Unité de Prévention et d'Epidémiologie Génétique; Centre Léon Bérard, 28 rue Laënnec; Lyon France, N.N. Petrov Institute of Oncology; St. Petersburg Russia, Department of Clinical Genetics; Royal Devon & Exeter Hospital; Exeter UK, Service de Génétique; Institut Curie, 26 rue d'Ulm; Paris France, Department of Medicine; Huntsman Cancer Institute; Salt Lake City USA, Molecular Oncology Laboratory; Hospital Clinico San Carlos; Instituto de Investigación Sanitaria San Carlos (IdISSC); Centro Investigación Biomédica en Red de Cáncer (CIBERONC); Madrid Spain, Institute of Human Genetics; University Hospital of Schleswig-Holstein; Kiel Germany, Section of Molecular Genetics, Dept. of Laboratory Medicine; University Hospital of Pisa; Pisa Italy, Research Division; Peter MacCallum Cancer Centre; Melbourne Australia, CRCHU de Quebec-oncologie, Centre des maladies du sein Deschênes-Fabia; Hôpital du Saint-Sacrement; Sainte-Foy Canada, Lombardi Comprehensive Cancer Center; Georgetown University; Washington USA, Departments of Pediatrics and Medicine; Columbia University; New York USA, Department of Clinical Genetics, Family Cancer Clinic; Erasmus University Medical Center; Rotterdam The Netherlands, Sheffield Clinical Genetics Service; Sheffield Children's Hospital; Sheffield UK, Department of Clinical Genetics; South Glasgow University Hospitals; Glasgow UK, Unité d'oncogénétique; ICO-Centre René Gauducheau; Saint Herblain France, Oncogenetics Group, Vall d'Hebron Institute of Oncology (VHIO), Clinical and Molecular Genetics Area; Vall d'Hebron University Hospital; Barcelona Spain, Department of Gynaecology and Obstetrics; Ludwig-Maximilian University; Munich Germany, Cáncer Hereditario, Instituto de Biología y Genética Molecular, IBGM; Universidad de Valladolid; Valladolid Spain, Institute of Human Genetics; University of Münster; Münster Germany, Nottingham Clinical Genetics Service; Nottingham University Hospitals NHS Trust; Nottingham UK, Oncogenetics Team; The Institute of Cancer Research and Royal Marsden NHS Foundation Trust; London UK, Department of Clinical Genetics; Lund University Hospital; Lund Sweden, Clinical Genetics; Guy's and St. Thomas’ NHS Foundation Trust; London UK, Department of Oncology, Rigshospitalet; Copenhagen University Hospital; Copenhagen Denmark, Institute for Medical Informatics, Statistics and Epidemiology; University of Leipzig; Leipzig Germany, Department of Gynaecology and Obstetrics, Division of Tumor Genetics, Klinikum rechts der Isar; Technical University; Munich Germany, Genomic Medicine, Manchester Academic Health Sciences Centre, Division of Evolution and Genomic Sciences; University of Manchester, Central Manchester University Hospitals NHS Foundation Trust; Manchester UK, Centre de Lutte Contre le Cancer Georges François Leclerc, France and Genomic and Immunotherapy Medical Institute; Dijon University Hospital; Dijon France, Molecular Diagnostic Unit, Hereditary Cancer Program, ICO-IDIBELL (Catalan Institute of Oncology-Bellvitge Biomedical Research Institute); Barcelona Spain, Laboratoire de Génétique Chromosomique; Hôtel Dieu Centre Hospitalier; Chambéry France, Department of Cancer Epidemiology and Genetics; Masaryk Memorial Cancer Institute; Brno Czech Republic, Columbus Cancer Council, Ohio State University; Columbus USA, Genetic Counseling Unit, Hereditary Cancer Program, IDIBGI (Institut d'Investigació Biomèdica de Girona); Catalan Institute of Oncology; Girona Spain, Oncogenetics Department; Barretos Cancer Hospital; Barretos Brazil, UCLA Schools of Medicine and Public Health, Division of Cancer Prevention & Control Research; Jonsson Comprehensive Cancer Center; Los Angeles USA, Cancer Risk and Prevention Clinic; Dana-Farber Cancer Institute; Boston USA, Centre of Familial Breast and Ovarian Cancer, Department of Medical Genetics, Institute of Human Genetics; University of Würzburg, Germany; Würzburg, Department of Clinical Genetics; Copenhagen Denmark, Service Régional Oncogénétique Poitou-Charentes; Centre Hospitalier; Niort France, Department of Molecular Medicine; University La Sapienza, and Istituto Pasteur - Fondazione Cenci-Bolognetti; Rome Italy, Bâtiment Cheney D; Centre Léon Bérard; Lyon France, Ontario Cancer Genetics Network: Lunenfeld-Tanenbaum Research Institute; Mount Sinai Hospital; Toronto Canada, Department of Pathology and Laboratory Medicine; University of Kansas Medical Center; Kansas City USA, Clinical Genetics Branch, DCEG, NCI; NIH; Bethesda USA, Parkville Familial Cancer Centre; Peter MacCallum Cancer Centre; Melbourne Australia, Hematology, oncology and transfusion medicine center, Dept. of Molecular and Regenerative Medicine; Vilnius University Hospital Santariskiu Clinics; Vilnius Lithuania, Department of Epidemiology, Cancer Prevention Institute of California; Fremont USA, Women's Cancer Program at the Samuel Oschin Comprehensive Cancer Institute; Cedars-Sinai Medical Center; Los Angeles USA, Division of Molecular Pathology; Department of Pathology; Hong Kong Sanatorium & Hospital; Happy Valley Hong Kong, Department of Gynecology and Obstetrics; Medical Faculty and University Hospital Carl Gustav Carus; Dresden Germany, Research Department, Peter MacCallum Cancer Centre, Melbourne, Victoria; Australia and The Sir Peter MacCallum Department of Oncology University of Melbourne; Parkville Australia, Department of Surgery; Daerim St. Mary's Hospital; Seoul Korea, The Gyneco-Oncology Department; Chaim Sheba Medical Center; Ramat Gan Israel, Servicio de Genética-CIBERER U705; Hospital de la Santa Creu i Sant Pau; Barcelona Spain, The Feinstein Institute for Medical Research; Manhasset USA, Department of Laboratory Medicine and Pathology; and Health Sciences Research; Rochester USA, Department of Surgery; Soonchunhyang University and Seoul Hospital; Seoul Korea, Inserm U900, Institut Curie; PSL Research University; Paris France, Department of Oncology Radiumhemmet and Institution of Oncology and Patology; Karolinska University Hospital and Karolinska Institutet; Solna Sweden, Department of Health Sciences Research; Mayo Clinic; Scottsdale USA, Oncogénétique; Institut Bergonié; Bordeaux France, Clinical Genetics Branch, DCEG, NCI, NIH; Bethesda USA, Department of Gynecological Oncology and Clinical Cancer Genetics Program; University Of Texas MD Anderson Cancer Center; Houston USA, Department of Dermatology; University of Utah School of Medicine; Salt Lake City USA, Centre Antoine Lacassagne; Nice France, Laboratorio de Genética Molecular, Servicio de Genética; Hospital Universitario Cruces, BioCruces Health Research Institute; Barakaldo Spain, Department of Surgery; National Institute of Oncology; Budapest Hungary, Department of Clinical Genetics; VU University Medical Center; Amsterdam The Netherlands, Department of Human Genetics; Radboud University Medical Center; Nijmegen The Netherlands, Vilnius university Santariskiu hospital; National Center of Pathology; Vilnius Lithuania, NRG Oncology; Statistics and Data Management Center; Roswell Park Cancer Institute; Buffalo USA, Department of Cancer Prevention and Control; Roswell Park Cancer Institute; Buffalo USA, Department of Laboratory Medicine and Pathobiology; University of Toronto; Toronto Canada, Department of Obstetrics and Gynecology; University of Helsinki and Helsinki University Hospital; HUS Finland, Cancer Genetics Service; Division of Medical Oncology; National Cancer Centre Singapore; Bukit Merah Singapore, Institute of Medical Genetics and Applied Genomics; University of Tuebingen; Tuebingen Germany, Molecular Oncology Research Center; Barretos Cancer Hospital; São Paulo Brazil, Cancer Genetics and Prevention Program; University of California San Francisco; San Francisco USA, Clinical Genetics Research Laboratory; Dept. of Medicine; Cancer Biology and Genetics; Memorial Sloan-Kettering Cancer Center; New York USA, Department of Clinical Genetics; Sahlgrenska University Hospital; Gothenburg Sweden, West Midlands Regional Genetics Service; Birmingham Women's Hospital Healthcare NHS Trust; Edgbaston UK, Human Genetics Group; Human Cancer Genetics Programme; Spanish National Cancer Research Centre (CNIO); Biomedical Network on Rare Diseases (CIBERER); Madrid Spain, Unit of Medical Genetics; Department of Biomedical; Experimental and Clinical Sciences; University of Florence; Florence Italy, Department of Medical Sciences; University of Turin; Turin Italy, Section of Molecular Diagnostics; Department of Biochemistry; Aalborg University Hospital; Aalborg Denmark, Department of Preventive Medicine; Seoul National University College of Medicine; Seoul Korea, IFOM; The FIRC (Italian Foundation for Cancer Research) Institute of Molecular Oncology; Milan Italy, Service de Génétique Clinique Chromosomique et Moléculaire; Hôpital Nord; St Etienne France, Unité d'Oncogénétique; CHU Arnaud de Villeneuve; Montpellier France, Unit of Molecular Bases of Genetic Risk and Genetic Testing; Department of Research; Fondazione IRCCS (Istituto Di Ricovero e Cura a Carattere Scientifico), Istituto Nazionale Tumori (INT); Milan Italy, School of Women's and Children's Health; UNSW; Sydney Australia, Department of Clinical Genetics; Karolinska University Hospital; Stockholm Sweden, Rebbeck, Timothy R., Friebel, Tara M., Friedman, Eitan, Hamann, Ute, Huo, Dezheng, Kwong, Ava, Olah, Edith, Olopade, Olufunmilayo I., Solano, Angela R., Teo, Soo-Hwang, Thomassen, Mads, Rashid, Muhammad Usman, Rhiem, Kerstin, Robson, Mark, Rodriguez, Gustavo C., Rogers, Mark T., Rudaitis, Vilius, Schmidt, Ane Y., Schmutzler, Rita Katharina, Senter, Leigha, van Rensburg, Elizabeth J., Gronwald, Jacek, Shah, Payal D., Sharma, Priyanka, Side, Lucy E., Simard, Jacques, Singer, Christian F., Skytte, Anne-Bine, Slavin, Thomas P., Snape, Katie, Sobol, Hagay, Southey, Melissa, Gutierrez-Barrera, Angelica, McGuffog, Lesley, Steele, Linda, Steinemann, Doris, Sukiennicki, Grzegorz, Sutter, Christian, Szabo, Csilla I., Tan, Yen Y., Teixeira, Manuel R., Terry, Mary Beth, Teulé, Alex, Hahnen, Eric, Thomas, Abigail, Parsons, Michael T., Thull, Darcy L., Tischkowitz, Marc, Tognazzo, Silvia, Toland, Amanda Ewart, Topka, Sabine, Trainer, Alison H, Tung, Nadine, van Asperen, Christi J., Hauke, Jan, van der Hout, Annemieke H., van der Kolk, Lizet E., Leslie, Goska, van der Luijt, Rob B., Van Heetvelde, Mattias, Varesco, Liliana, Varon-Mateeva, Raymonda, Vega, Ana, Villarreal-Garza, Cynthia, von Wachenfeldt, Anna, Henderson, Alex, Walker, Lisa, Wang-Gohrke, Shan, Wappenschmidt, Barbara, Aalfs, Cora M., Weber, Bernhard H. F., Yannoukakos, Drakoulis, Yoon, Sook-Yee, Zanzottera, Cristina, Zidan, Jamal, Zorn, Kristin K., Hentschel, Julia, Hutten Selkirk, Christina G., Hulick, Peter J., Chenevix-Trench, Georgia, Spurdle, Amanda B., Abugattas, Julio, Antoniou, Antonis C., Nathanson, Katherine L., Adlard, Julian, Agata, Simona, Aittomäki, Kristiina, Hogervorst, Frans B.L., Andrews, Lesley, Andrulis, Irene L., Arason, Adalgeir, Arnold, Norbert, Arun, Banu K., Asseryanis, Ella, Auerbach, Leo, Azzollini, Jacopo, Balmaña, Judith, Barile, Monica, Honisch, Ellen, Barkardottir, Rosa B., Barrowdale, Daniel, Benitez, Javier, Berger, Andreas, Berger, Raanan, Blanco, Amie M., Blazer, Kathleen R., Blok, Marinus J., Bonadona, Valérie, Bonanni, Bernardo, Imyanitov, Evgeny N., Bradbury, Angela R., Brewer, Carole, Buecher, Bruno, Buys, Saundra S., Caldes, Trinidad, Caliebe, Almuth, Caligo, Maria A., Campbell, Ian, Caputo, Sandrine M., Chiquette, Jocelyne, Isaacs, Claudine, Chung, Wendy K., Claes, Kathleen B.M., Collée, J. Margriet, Cook, Jackie, Davidson, Rosemarie, de la Hoya, Miguel, De Leeneer, Kim, de Pauw, Antoine, Delnatte, Capucine, Diez, Orland, Weitzel, Jeffrey N., Ding, Yuan Chun, Ditsch, Nina, Domchek, Susan M., Dorfling, Cecilia M., Velazquez, Carolina, Dworniczak, Bernd, Eason, Jacqueline, Easton, Douglas F., Eeles, Ros, Ehrencrona, Hans, Izatt, Louise, Ejlertsen, Bent, Engel, Christoph, Engert, Stefanie, Evans, D. Gareth, Faivre, Laurence, Feliubadaló, Lidia, Ferrer, Sandra Fert, Foretova, Lenka, Fowler, Jeffrey, Frost, Debra, Izquierdo, Angel, Galvão, Henrique C. R., Ganz, Patricia A., Garber, Judy, Gauthier-Villars, Marion, Gehrig, Andrea, Gerdes, Anne-Marie, Gesta, Paul, Giannini, Giuseppe, Giraud, Sophie, Glendon, Gord, Jakubowska, Anna, Godwin, Andrew K., Greene, Mark H., James, Paul, Janavicius, Ramunas, Jensen, Uffe Birk, John, Esther M., Vijai, Joseph, Kaczmarek, Katarzyna, Karlan, Beth Y., Chan, TL, Kast, Karin, Investigators, KConFab, Kim, Sung-Won, Konstantopoulou, Irene, Korach, Jacob, Laitman, Yael, Lasa, Adriana, Lasset, Christine, Lázaro, Conxi, Lee, Annette, Couch, Fergus J., Lee, Min Hyuk, Lester, Jenny, Lesueur, Fabienne, Liljegren, Annelie, Lindor, Noralane M., Longy, Michel, Loud, Jennifer T., Lu, Karen H., Lubinski, Jan, Machackova, Eva, Goldgar, David E., Manoukian, Siranoush, Mari, Véronique, Martínez-Bouzas, Cristina, Matrai, Zoltan, Mebirouk, Noura, Meijers-Heijboer, Hanne E.J., Meindl, Alfons, Mensenkamp, Arjen R., Mickys, Ugnius, Miller, Austin, Kruse, Torben A., Montagna, Marco, Moysich, Kirsten B., Mulligan, Anna Marie, Musinsky, Jacob, Neuhausen, Susan L., Nevanlinna, Heli, Ngeow, Joanne, Nguyen, Huu Phuc, Niederacher, Dieter, Nielsen, Henriette Roed, Palmero, Edenir Inêz, Nielsen, Finn Cilius, Nussbaum, Robert L., Offit, Kenneth, Öfverholm, Anna, Ong, Kai-ren, Osorio, Ana, Papi, Laura, Papp, Janos, Pasini, Barbara, Pedersen, Inge Sokilde, Park, Sue Kyung, Peixoto, Ana, Peruga, Nina, Peterlongo, Paolo, Pohl, Esther, Pradhan, Nisha, Prajzendanc, Karolina, Prieur, Fabienne, Pujol, Pascal, Radice, Paolo, Ramus, Susan J., Torres, Diana, and Rantala, Johanna
Abstract: To access publisher's full text version of this article click on the hyperlink below, The prevalence and spectrum of germline mutations in BRCA1 and BRCA2 have been reported in single populations, with the majority of reports focused on White in Europe and North America. The Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA) has assembled data on 18,435 families with BRCA1 mutations and 11,351 families with BRCA2 mutations ascertained from 69 centers in 49 countries on six continents. This study comprehensively describes the characteristics of the 1,650 unique BRCA1 and 1,731 unique BRCA2 deleterious (disease-associated) mutations identified in the CIMBA database. We observed substantial variation in mutation type and frequency by geographical region and race/ethnicity. In addition to known founder mutations, mutations of relatively high frequency were identified in specific racial/ethnic or geographic groups that may reflect founder mutations and which could be used in targeted (panel) first pass genotyping for specific populations. Knowledge of the population-specific mutational spectrum in BRCA1 and BRCA2 could inform efficient strategies for genetic testing and may justify a more broad-based oncogenetic testing in some populations.

16. Secourons nos frères! [Música notada] : cantate pour des inondés du Midi avec choeur, soli et orchestre ou piano

Author: Deslandres, Adolphe 1840-1911, St. Etienne, Sylvain, Deslandres, Adolphe 1840-1911, and St. Etienne, Sylvain
Abstract: Fecha de publicación basada en el Dictionnaire des éditeurs de musique français, volume II, de 1820 à 1914, 1988

17. Secourons nos frères! [Música notada] : cantate pour des inondés du Midi avec choeur, soli et orchestre ou piano

Author: Deslandres, Adolphe 1840-1911, St. Etienne, Sylvain, Deslandres, Adolphe 1840-1911, and St. Etienne, Sylvain
Abstract: Fecha de publicación basada en el Dictionnaire des éditeurs de musique français, volume II, de 1820 à 1914, 1988

18. Low-tech approaches for sustainability: key principles from the literature and practice

Author: Audrey Tanguy, Lisa Carrière, Valérie Laforest, École des Mines de Saint-Étienne (Mines Saint-Étienne MSE), Institut Mines-Télécom [Paris] (IMT), Institut Henri Fayol (FAYOL-ENSMSE), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), Environnement, Ville, Société (EVS), École normale supérieure de Lyon (ENS de Lyon)-École des Mines de Saint-Étienne (Mines Saint-Étienne MSE), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Université Lumière - Lyon 2 (UL2)-Université Jean Moulin - Lyon 3 (UJML), Université de Lyon-Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Jean Monnet - Saint-Étienne (UJM)-École Nationale des Travaux Publics de l'État (ENTPE)-École nationale supérieure d'architecture de Lyon (ENSAL)-Centre National de la Recherche Scientifique (CNRS), Département Génie de l’environnement et des organisations (FAYOL-ENSMSE), and Institut Henri Fayol-Ecole Nationale Supérieure des Mines de St Etienne (ENSM ST-ETIENNE)
Subjects: Geography, Planning and Development, development pathways, [SDE]Environmental Sciences, Low-tech, defining framework, principles, sustainability, General Environmental Science
Abstract: Low-tech approaches have come to the fore in the last few years, mainly in opposition to the techno-optimistic model proposed to solve current and future environmental crises. However, low-tech thinking is multifaceted, making the concept potentially rich but also vague. This article develops a seven-principle framework to categorize low-tech concepts based on an abductive approach which included a literature review and interviews with low-tech actors. Principle occurrence was assessed among the authors and interviewees. The results demonstrate that the low-tech movement entails more than a shift to robust and less-consumptive technical artifacts. While resource efficiency and material reuse are important traits of low-tech approaches, technical appropriation is the most frequently cited key principle in the literature and by the actors. This delineation into several principles can help to differentiate low-tech from other sustainability concepts related to resource conservation such as frugal innovations and circular economy. We aim in this article to open a discussion about the ways low-tech proponents are seeking to introduce transformative development pathways to sustainability.
Published: 2023

19. Recovering Headerless Frames in LR-FHSS

Author: Fraire, Juan Andrés, Guitton, Alexandre, Iova, Oana, ALGorithmes et Optimisation pour Réseaux Autonomes (AGORA), Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-CITI Centre of Innovation in Telecommunications and Integration of services (CITI), Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA), Consejo Nacional de Investigaciones Científicas y Técnicas [Buenos Aires] (CONICET), Saarland University [Saarbrücken], AlGorithmes et Optimisation pour Réseaux Autonomes (AGORA), CITI Centre of Innovation in Telecommunications and Integration of services (CITI), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Inria Lyon, Institut National de Recherche en Informatique et en Automatique (Inria), Laboratoire d'Informatique, de Modélisation et d'Optimisation des Systèmes (LIMOS), Ecole Nationale Supérieure des Mines de St Etienne (ENSM ST-ETIENNE)-Centre National de la Recherche Scientifique (CNRS)-Université Clermont Auvergne (UCA)-Institut national polytechnique Clermont Auvergne (INP Clermont Auvergne), Université Clermont Auvergne (UCA)-Université Clermont Auvergne (UCA), Université Clermont Auvergne (UCA), ANR-22-CE25-0014,STEREO,Convergence IoT - Satellite(2022), ANR-21-CE25-0002,DOLL,DOLL: Communication DOwnLink efficace pour une capacité LoRaWAN augmenté(2021), and European Project: 101008233 ,MISSION
Subjects: Networking and Internet Architecture (cs.NI), FOS: Computer and information sciences, Computer Science - Networking and Internet Architecture, ILP, satellite IoT, [INFO.INFO-NI]Computer Science [cs]/Networking and Internet Architecture [cs.NI], headerless frames, Frame recovery, LR-FHSS, [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation
Abstract: International audience; Long-Range Frequency Hopping Spread Spectrum (LR-FHSS) is a recent modulation designed for communications from low-power ground end-devices to Low-Earth Orbit (LEO) satellites. To decode a frame, an LR-FHSS gateway must receive at least one header replica and a large proportion of payload fragments. However, LR-FHSS headers will likely be lost when there are many concurrent transmissions. In this paper, we motivate the header loss problem with an analytical model, propose a linear programming model to extract headerless frames and design a cost-effective sliding window heuristic. Simulation results show that our approach exhibits near-optimal headerless detection and extraction results while ensuring a low computational cost. The proposed method is, therefore, suitable for future LR-FHSS gateways located onboard resource-constrained LEO satellites.
Published: 2023

20. Secure protocols for cumulative reward maximization in stochastic multi-armed bandits

Author: Ciucanu, Radu, Lafourcade, Pascal, Lombard-Platet, Marius, Soare, Marta, Laboratoire d'Informatique de Grenoble (LIG), Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA), Laboratoire d'Informatique, de Modélisation et d'Optimisation des Systèmes (LIMOS), Ecole Nationale Supérieure des Mines de St Etienne (ENSM ST-ETIENNE)-Centre National de la Recherche Scientifique (CNRS)-Université Clermont Auvergne (UCA)-Institut national polytechnique Clermont Auvergne (INP Clermont Auvergne), Université Clermont Auvergne (UCA)-Université Clermont Auvergne (UCA), Département d'informatique - ENS Paris (DI-ENS), École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS), ANR-19-P3IA-0003,MIAI,MIAI @ Grenoble Alpes(2019), European Project: H2020,INODE, and European Project: 952215,TAILOR(2020)
Subjects: [INFO.INFO-CR]Computer Science [cs]/Cryptography and Security [cs.CR], [INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB], [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG], Computer Networks and Communications, Hardware and Architecture, Safety, Risk, Reliability and Quality, Software, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]
Abstract: International audience; We consider the problem of cumulative reward maximization in multi-armed bandits. We address the security concerns that occur when data and computations are outsourced to an honest-but-curious cloud i.e., that executes tasks dutifully, but tries to gain as much information as possible. We consider situations where data used in bandit algorithms is sensitive and has to be protected e.g., commercial or personal data. We rely on cryptographic schemes and propose UCB - MS, a secure multi-party protocol based on the UCB algorithm. We prove that UCB - MS computes the same cumulative reward as UCB while satisfying desirable security properties. In particular, cloud nodes cannot learn the cumulative reward or the sum of rewards for more than one arm. Moreover, by analyzing messages exchanged among cloud nodes, an external observer cannot learn the cumulative reward or the sum of rewards produced by some arm. We show that the overhead due to cryptographic primitives is linear in the size of the input. Our implementation confirms the linear-time behavior and the practical feasibility of our protocol, on both synthetic and real-world data.
Published: 2023

21. Evaluating the scalability of reconfigurable manufacturing systems at the design phase

Author: Audrey Cerqueus, Xavier Delorme, Département Automatique, Productique et Informatique (IMT Atlantique - DAPI), IMT Atlantique (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), Modélisation, Optimisation et DEcision pour la Logistique, l'Industrie et les Services (LS2N - équipe MODELIS), Laboratoire des Sciences du Numérique de Nantes (LS2N), Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-École Centrale de Nantes (Nantes Univ - ECN), Nantes Université (Nantes Univ)-Nantes Université (Nantes Univ)-Nantes université - UFR des Sciences et des Techniques (Nantes univ - UFR ST), Nantes Université - pôle Sciences et technologie, Nantes Université (Nantes Univ)-Nantes Université (Nantes Univ)-Nantes Université - pôle Sciences et technologie, Nantes Université (Nantes Univ)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique), Nantes Université (Nantes Univ), Laboratoire d'Informatique, de Modélisation et d'Optimisation des Systèmes (LIMOS), Ecole Nationale Supérieure des Mines de St Etienne (ENSM ST-ETIENNE)-Centre National de la Recherche Scientifique (CNRS)-Université Clermont Auvergne (UCA)-Institut national polytechnique Clermont Auvergne (INP Clermont Auvergne), Université Clermont Auvergne (UCA)-Université Clermont Auvergne (UCA), Département Génie mathématique et industriel (FAYOL-ENSMSE), Ecole Nationale Supérieure des Mines de St Etienne (ENSM ST-ETIENNE)-Institut Henri Fayol, Institut Henri Fayol (FAYOL-ENSMSE), École des Mines de Saint-Étienne (Mines Saint-Étienne MSE), Institut Mines-Télécom [Paris] (IMT), and ANR-21-CE10-0019,RECONFIDURABLE,Conception et pilotage de systèmes de production reconfigurables et durables(2021)
Subjects: Combinatorial analysis, Strategy and Management, Scalability, Line Balancing, [INFO]Computer Science [cs], Multi-objective indicator, Management Science and Operations Research, [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation, Industrial and Manufacturing Engineering, Reconfigurable manufacturing systems
Abstract: International audience; To face market volatility, reconfigurable manufacturing systems (RMS) aim to efficiently and cost-effectively react to changes. We focus on one characteristic of RMS: the scalability (ability to adapt the volume of throughput). In the literature, the only few indicators for scalability are not always formally defined and usually only consider a partial view of scalability. Moreover, most of them are actually more suited for the configuration planning rather than for the design. However, the design of the RMS has a high impact on its scalability. We propose the first combinatorial definition of this problem and a new measure to fully assess the scalability of a system at the design phase. This measure, based on a multi-objective approach, can assess the scalability of single-product manufacturing systems, analysing all configurations that it can implement. We present numerical experiments to compare this indicator with a state-of-the-art scalability indicator and with some classical production line design indicators, and we show that future research should focus on scalability as a specific criterion to optimise during the design of an RMS. In addition, the results obtained allow us to infer some managerial insights on the best levers to use when performing a reconfiguration for scalability purpose.
Published: 2023

22. Opportunities and Challenges of LoRa 2.4 GHz

Author: HOCHET DEREVIANCKINE, Gwendoline, Guitton, Alexandre, Iova, Oana, Ning, Baozhu, Valois, Fabrice, AlGorithmes et Optimisation pour Réseaux Autonomes (AGORA), CITI Centre of Innovation in Telecommunications and Integration of services (CITI), Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Inria Lyon, Institut National de Recherche en Informatique et en Automatique (Inria), Laboratoire d'Informatique, de Modélisation et d'Optimisation des Systèmes (LIMOS), Ecole Nationale Supérieure des Mines de St Etienne (ENSM ST-ETIENNE)-Centre National de la Recherche Scientifique (CNRS)-Université Clermont Auvergne (UCA)-Institut national polytechnique Clermont Auvergne (INP Clermont Auvergne), Université Clermont Auvergne (UCA)-Université Clermont Auvergne (UCA), Semtech (Meylan, France), and Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)
Subjects: protocol design, [INFO.INFO-NI]Computer Science [cs]/Networking and Internet Architecture [cs.NI], protocol comparison, Computer Networks and Communications, LoRa 2.4 GHz, Electrical and Electronic Engineering, LoRaWAN, Computer Science Applications
Abstract: International audience; Internet of Things (IoT) technologies are increasingly used in our daily life. Among these technologies, LoRa is widely used for low power IoT data collection in wide areas. LoRa typically operates in sub-GHz bands which are region-specific, and thus has limited worldwide applications. The version of LoRa developed for the 2.4 GHz ISM band has spurred recent interest in the scientific community, as it enables the use of worldwide frequency channels. However, it requires the coexistence with numerous concurrent technologies within this 2.4 GHz band, and an evolution of the MAC and networking protocols for utilizing LoRaWAN connectivity. In this paper, we make the first experimental comparison between LoRa sub-GHz and LoRa 2.4 GHz in both indoor and outdoor scenarios. We show that LoRa 2.4 GHz can have a communication range of more than 2 km outdoor, and it can achieve a packet delivery rate of at least 0.98 for a distance of up to 39 meters indoor with the presence of obstacles. We also make an extensive discussion on the researches challenges that need to be addressed in order to fully take advantage of this new technology.
Published: 2023

23. Data-centric UML profile for agroecology applications: Agricultural autonomous robots monitoring case study

Author: Sandro Bimonte, Hassan Badir, Pietro Battistoni, Houssam Bazza, Amina Belhassena, Christophe Cariou, Gerard Chalhoub, Juan Corrales, Adrian Couvent, Jean Laneurit, Rim Moussa, Julian Plazas, Monica Sebillo, Nicolas Tricot, Laboratoire d'Informatique, de Modélisation et d'Optimisation des Systèmes (LIMOS), and Ecole Nationale Supérieure des Mines de St Etienne (ENSM ST-ETIENNE)-Université Clermont Auvergne [2017-2020] (UCA [2017-2020])-Centre National de la Recherche Scientifique (CNRS)
Subjects: General Computer Science, [INFO]Computer Science [cs]
Abstract: International audience; The conceptual design of information systems is mandatory in several application domains. The advent of the Internet of Things (IoT) technologies pushes conceptual design tools and methodologies to consider the complexity of IoT data, architectures, and communication networks. In agroecology applications, the usage of IoT is quite promising, but it raises several methodological and technical issues. These issues are related to the complexity and heterogeneity of data (social, economic, environmental, and agricultural) needed by agroecology practices. Motivated by the lack of a conceptual model for IoT data, in this work, we present a UML profile taking into account different kinds of data (e.g., sensors, stream, or transactional) and non-functional Requirements. We show how the UML profile integrates with classical UML diagrams to support the design of complex systems. Moreover, We prove the feasibility of our conceptual framework through a theoretical quality assessment and its implementation in the agroecology case study concerning the monitoring of autonomous agricultural robots.
Published: 2023

24. Multi-objective collaborative assembly line design problem with the optimisation of ergonomics and economics

Author: Mohammed-Amine Abdous, Xavier Delorme, Daria Battini, Sandrine Berger-Douce, Centre for Digital Systems (CERI SN - IMT Nord Europe), Ecole nationale supérieure Mines-Télécom Lille Douai (IMT Nord Europe), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), Institut Mines-Télécom [Paris] (IMT), École des Mines de Saint-Étienne (Mines Saint-Étienne MSE), Institut Henri Fayol (FAYOL-ENSMSE), Département Génie mathématique et industriel (FAYOL-ENSMSE), Ecole Nationale Supérieure des Mines de St Etienne (ENSM ST-ETIENNE)-Institut Henri Fayol, Laboratoire d'Informatique, de Modélisation et d'Optimisation des Systèmes (LIMOS), Ecole Nationale Supérieure des Mines de St Etienne (ENSM ST-ETIENNE)-Centre National de la Recherche Scientifique (CNRS)-Université Clermont Auvergne (UCA)-Institut national polytechnique Clermont Auvergne (INP Clermont Auvergne), Université Clermont Auvergne (UCA)-Université Clermont Auvergne (UCA), Université de Padoue, COnception de l'ACTIon en Situation (COACTIS), Université Lumière - Lyon 2 (UL2)-Université Jean Monnet - Saint-Étienne (UJM), and Département Management responsable et innovation (FAYOL-ENSMSE)
Subjects: ergonomics, Strategy and Management, multi-objective optimisation, Assembly line balancing problem, assembly line design problem, Industry 4.0, Industry 5.0, Management Science and Operations Research, [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation, Industrial and Manufacturing Engineering
Abstract: International audience; Manufacturing systems are socio-technical systems, with explicit interactions between humans and technologies in shared workspaces. These shared workspaces could also be called hybrid collaborative manufacturing systems, which involve workers as well as technological equipment and combine the benefits of human workers and new Industry 4.0 technologies, such systems are particularly useful in a context requiring flexibility and adaptability. Furthermore, the new Industry 5.0 approach has the objective to shift toward more human-centric and resilient manufacturing systems. The key problems to solve in the design of collaborative manufacturing systems are the combinatorial assembly line balancing problem and the equipment selection problem. An efficient and sustainable line requires a cost-effective choice of equipment while improving the ergonomics and the safety of workers. Both decisions of balancing workload and the assignment of equipment impact the ergonomics of a collaborative system and present conflicting criteria. To this end, we propose a multi-objective approach, the objectives are the optimisation of the investment costs and the ergonomics with a fatigue and recovery criterion. We propose to linearise the fatigue and recovery to formulate a new Mixed Integer Linear Programming formulation. We developed an exact multi-objective solving algorithm based on the ϵ-constraint to obtain the trade-off between these objectives. We conducted numerical experiments with different instances from the literature with promising results for instances with up to 45 operations. Finally, we discuss insightful managerial conclusions and future research perspectives.
Published: 2022

25. Proofs and Certificates for Max-SAT

Author: Matthieu Py, Mohamed Sami Cherif, Djamal Habet, COntraintes, ALgorithmes et Applications (COALA), Laboratoire d'Informatique et Systèmes (LIS), Aix Marseille Université (AMU)-Université de Toulon (UTLN)-Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-Université de Toulon (UTLN)-Centre National de la Recherche Scientifique (CNRS), Laboratoire d'Informatique, de Modélisation et d'Optimisation des Systèmes (LIMOS), Ecole Nationale Supérieure des Mines de St Etienne (ENSM ST-ETIENNE)-Centre National de la Recherche Scientifique (CNRS)-Université Clermont Auvergne (UCA)-Institut national polytechnique Clermont Auvergne (INP Clermont Auvergne), and Université Clermont Auvergne (UCA)-Université Clermont Auvergne (UCA)
Subjects: Artificial Intelligence, [INFO]Computer Science [cs]
Abstract: International audience; Current Max-SAT solvers are able to efficiently compute the optimal value of an input instance but they do not provide any certificate of its validity. In this paper, we present a tool, called MS-Builder, which generates certificates for the Max-SAT problem in the particular form of a sequence of equivalence-preserving transformations. To generate a certificate, MS-Builder iteratively calls a SAT oracle to get a SAT resolution refutation which is handled and adapted into a sound refutation for Max-SAT. In particular, we prove that the size of the computed Max-SAT refutation is linear with respect to the size of the initial refutation if it is semi-read-once, tree-like regular, tree-like or semi-tree-like. Additionally, we propose an extendable tool, called MS-Checker, able to verify the validity of any Max-SAT certificate using Max-SAT inference rules. Both tools are evaluated on the unweighted and weighted benchmark instances of the 2020 Max-SAT Evaluation.
Published: 2022

26. Stokes and Navier-Stokes equations under power law slip boundary condition: Numerical analysis

Author: J.K. Djoko, J. Koko, M. Mbehou, Toni Sayah, African Peer Review Mechanism, Laboratoire d'Informatique, de Modélisation et d'Optimisation des Systèmes (LIMOS), Ecole Nationale Supérieure des Mines de St Etienne (ENSM ST-ETIENNE)-Centre National de la Recherche Scientifique (CNRS)-Université Clermont Auvergne (UCA)-Institut national polytechnique Clermont Auvergne (INP Clermont Auvergne), Université Clermont Auvergne (UCA)-Université Clermont Auvergne (UCA), Département de Mathématiques Université de Yaoundé 1 = Department of Mathematics [Yaoundé, Cameroon], Université de Yaoundé I, Université Saint-Joseph de Beyrouth (USJ), and Kamdem, Djoko
Subjects: power law slip boundary condition, finite element method, Stokes equations, [MATH] Mathematics [math], [MATH.MATH-NA] Mathematics [math]/Numerical Analysis [math.NA], monotonicity, Computational Mathematics, Computational Theory and Mathematics, error estimates, Modeling and Simulation, Navier-Stokes equations, [MATH]Mathematics [math], [MATH.MATH-NA]Mathematics [math]/Numerical Analysis [math.NA], rate of convergence
Abstract: International audience; In this work, we study theoretically and numerically the equations of Stokes and Navier-Stokes under power law slip boundary condition. We establish existence of a unique solution by using the monotone operators theory for the Stokes equations whereas for the Navier-Stokes equations, we construct the solution by means of Galerkin's approximation combined with some compactness results. Next, we formulate and analyze the finite element approximations associated to these problems. We derive optimal and sub-optimal a priori error estimate for both problems depending how the monotonicity is used. Iterative schemes for solving the nonlinear problems are formulated and convergence is studied. Numerical experiments presented confirm the theoretical findings.
Published: 2022

27. Mean Field Game-Theoretic Framework for Distributed Power Control in Hybrid NOMA

Author: Amani Benamor, Oussama Habachi, Ines Kammoun, Jean-Pierre Cances, XLIM (XLIM), Université de Limoges (UNILIM)-Centre National de la Recherche Scientifique (CNRS), Laboratoire d'électronique et des technologies de l'Information [Sfax] (LETI), École Nationale d'Ingénieurs de Sfax | National School of Engineers of Sfax (ENIS), Laboratoire d'Informatique, de Modélisation et d'Optimisation des Systèmes (LIMOS), Ecole Nationale Supérieure des Mines de St Etienne (ENSM ST-ETIENNE)-Centre National de la Recherche Scientifique (CNRS)-Université Clermont Auvergne (UCA)-Institut national polytechnique Clermont Auvergne (INP Clermont Auvergne), Université Clermont Auvergne (UCA)-Université Clermont Auvergne (UCA), and ANR-20-CE25-0004,MOMENT,Accès Massif pour les Réseaux 5G et au-delà(2020)
Subjects: Applied Mathematics, [INFO]Computer Science [cs], Electrical and Electronic Engineering, Computer Science Applications
Abstract: International audience; The steady expansion of the number of wireless devices and the ubiquity of the networks give rise to various interesting challenges for the future sixth generation (6G) of wireless communication systems. Particularly, the operators have to handle massive connectivity among Machine Type Devices (MTDs) and increasing demand for eMMB through limited spectrum resources. Non-Orthogonal Multiple Access (NOMA) has been spotlighted as an emerging technology to meet the above-mentioned challenges. In this paper, we consider a densely deployed network in which users are divided into NOMA coalitions. Firstly, we model the power allocation problem as a differential game. Then, we extend the formulated game using a Mean Field Game (MFG) theoretic framework by considering the effect of the collective behavior of devices. Furthermore, we derive a distributed power control algorithm that enables the users to appropriately regulate their transmit power according to brief information received from the BS. Indeed, the analysis of the proposed approach is governed by the two fundamental Hamilton- Jacobi-Bellman (HJB) and Fokker-Planck-Kolmogorov (FPK) equations. Numerical results are presented to analyze the equilibrium behaviors of the proposed power control algorithm and to demonstrate the effectiveness of the formulated MFG compared to existing works in the literature.
Published: 2022

28. Letter Graphs and Geometric Grid Classes of Permutations

Author: Bogdan Alecu, Robert Ferguson, Mamadou Moustapha Kanté, Vadim V. Lozin, Vincent Vatter, Victor Zamaraev, Warwick Mathematics Institute (WMI), University of Warwick [Coventry], Department of Mathematics [Gainesville] (UF|Math), University of Florida [Gainesville] (UF), Laboratoire d'Informatique, de Modélisation et d'Optimisation des Systèmes (LIMOS), Ecole Nationale Supérieure des Mines de St Etienne (ENSM ST-ETIENNE)-Centre National de la Recherche Scientifique (CNRS)-Université Clermont Auvergne (UCA)-Institut national polytechnique Clermont Auvergne (INP Clermont Auvergne), and Université Clermont Auvergne (UCA)-Université Clermont Auvergne (UCA)
Subjects: inversion graphs permutation patterns well-quasi-order, General Mathematics, FOS: Mathematics, Mathematics - Combinatorics, Combinatorics (math.CO), [INFO.INFO-DM]Computer Science [cs]/Discrete Mathematics [cs.DM]
Abstract: International audience; We uncover a connection between two seemingly unrelated notions: lettericity, from structural graph theory, and geometric griddability, from the world of permutation patterns. Both of these notions capture important structural properties of their respective classes of objects. We prove that these notions are equivalent in the sense that a permutation class is geometrically griddable if and only if the corresponding class of inversion graphs has bounded lettericity.
Published: 2022

29. A scalable Matérn Gaussian process for learning spatial curves distributions

Author: Tran, Tam Tien, Feunteun, Yan, Samir, Chafik, Braga, José, Laboratoire d'Informatique, de Modélisation et d'Optimisation des Systèmes (LIMOS), Ecole Nationale Supérieure des Mines de St Etienne (ENSM ST-ETIENNE)-Centre National de la Recherche Scientifique (CNRS)-Université Clermont Auvergne (UCA)-Institut national polytechnique Clermont Auvergne (INP Clermont Auvergne), Université Clermont Auvergne (UCA)-Université Clermont Auvergne (UCA), Ecole Nationale Supérieure des Mines de St Etienne (ENSM ST-ETIENNE)-Université Clermont Auvergne [2017-2020] (UCA [2017-2020])-Centre National de la Recherche Scientifique (CNRS), Université Toulouse III - Paul Sabatier (UT3), and Université de Toulouse (UT)
Subjects: Information Systems and Management, Artificial Intelligence, Control and Systems Engineering, Gaussian process prior Maniflods Statistical shape analysis Learning on nonlinear manifolds Regression and classification, Software, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI], Computer Science Applications, Theoretical Computer Science
Abstract: International audience; Data points on Riemannian manifolds are fundamental objects in many applications and fields. Representations include shapes from biology and medical imaging, directions and rotations from robots. This paper addresses the problem of nonparametric regression on shapes when only few observations are available. In particular, we consider the problem of classifying unobserved 3D open parametrized curves using a continuous stochastic process to overcome the discrete nature of observations. The proposed method has a practical objective, characterizing populations of cochlear curves. The numerical solution is geometrically simpler, extensible and can be generalized for other applications. We illustrate and discuss the successful behavior of the proposed approach with various and multiple experimental results.
Published: 2022

30. Dynamic lot sizing with stochastic demand timing

Author: Stéphane Dauzère-Pérès, Kerem Akartunali, University of Strathclyde [Glasgow], Département Sciences de la Fabrication et Logistique (SFL-ENSMSE), École des Mines de Saint-Étienne (Mines Saint-Étienne MSE), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-CMP-GC, Laboratoire d'Informatique, de Modélisation et d'Optimisation des Systèmes (LIMOS), Ecole Nationale Supérieure des Mines de St Etienne (ENSM ST-ETIENNE)-Centre National de la Recherche Scientifique (CNRS)-Université Clermont Auvergne (UCA)-Institut national polytechnique Clermont Auvergne (INP Clermont Auvergne), Université Clermont Auvergne (UCA)-Université Clermont Auvergne (UCA), BI Norwegian Business School [Oslo], and Institut Mines-Télécom [Paris] (IMT)
Subjects: Lot Sizing, Dynamic Programming, Information Systems and Management, General Computer Science, Modeling and Simulation, Stochastic Demand Timing, HD28, Production, [INFO.INFO-RO]Computer Science [cs]/Operations Research [cs.RO], Management Science and Operations Research, ComputingMilieux_MISCELLANEOUS, Industrial and Manufacturing Engineering
Abstract: In this paper, a novel way of modeling uncertainty on demand in the single item dynamic lot sizing problem is proposed and studied. The uncertainty is not related to the demand quantity, but rather to the demand timing, i.e., the demand fully occurs in a single period of a given time interval with a given probability and no partial delivery is allowed. The problem is first motivated and modeled. Our modeling naturally correlates uncertain demands in different periods contrary to most of the literature in lot sizing. Dynamic programs are then proposed for the general case of multiple demands with stochastic demand timing and for several special cases. We also show that the most general case where the backlog cost depends both on the time period and the stochastic demand is NP-hard.
Published: 2022

31. The consistent electric-Vehicle routing problem with backhauls and charging management

Author: Pamela C. Nolz, Nabil Absi, Dominique Feillet, Clóvis Seragiotto, St. Pölten University of Applied Sciences, Laboratoire d'Informatique, de Modélisation et d'Optimisation des Systèmes (LIMOS), Ecole Nationale Supérieure des Mines de St Etienne (ENSM ST-ETIENNE)-Centre National de la Recherche Scientifique (CNRS)-Université Clermont Auvergne (UCA)-Institut national polytechnique Clermont Auvergne (INP Clermont Auvergne), Université Clermont Auvergne (UCA)-Université Clermont Auvergne (UCA), Département Sciences de la Fabrication et Logistique (SFL-ENSMSE), École des Mines de Saint-Étienne (Mines Saint-Étienne MSE), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-CMP-GC, Austrian Institute of Technology [Vienna] (AIT), and The project EUFAL is funded by the ERA-NET Cofund Electric Mobility Europe (EMEurope). EMEurope is co-funded by the European Commission within the research and innovation framework programme Horizon 2020 and national and regional funding organizations (Project No. 723977)
Subjects: Information Systems and Management, General Computer Science, Modeling and Simulation, [INFO.INFO-RO]Computer Science [cs]/Operations Research [cs.RO], Management Science and Operations Research, ComputingMilieux_MISCELLANEOUS, Industrial and Manufacturing Engineering
Abstract: International audience
Published: 2022

32. A distributed and incremental algorithm for large-scale graph clustering

Author: Wissem Inoubli, Sabeur Aridhi, Haithem Mezni, Mondher Maddouri, Engelbert Mephu Nguifo, Université de Tunis El Manar (UTM), Computational Algorithms for Protein Structures and Interactions (CAPSID), Inria Nancy - Grand Est, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Department of Complex Systems, Artificial Intelligence & Robotics (LORIA - AIS), Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS), Strategies for Modelling and ARtificial inTelligence Laboratory (SMART-LAB), Université de Tunis, University of Jeddah, Laboratoire d'Informatique, de Modélisation et d'Optimisation des Systèmes (LIMOS), Ecole Nationale Supérieure des Mines de St Etienne (ENSM ST-ETIENNE)-Université Clermont Auvergne [2017-2020] (UCA [2017-2020])-Centre National de la Recherche Scientifique (CNRS), This work was partially supported by the CNRS-INRIA/FAPs project 'TempoGraphs' (PRC2243)., Tallinn University, Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS), Université de Jendouba (UJ), Taibah University, Université Clermont Auvergne (UCA), Ecole Nationale Supérieure des Mines de St Etienne (ENSM ST-ETIENNE)-Centre National de la Recherche Scientifique (CNRS)-Université Clermont Auvergne (UCA)-Institut national polytechnique Clermont Auvergne (INP Clermont Auvergne), Université Clermont Auvergne (UCA)-Université Clermont Auvergne (UCA), and Ecole Nationale Supérieure des Mines de St Etienne-Université Clermont Auvergne [2017-2020] (UCA [2017-2020])-Centre National de la Recherche Scientifique (CNRS)
Subjects: Big Data, [INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB], Community detection, Computer Networks and Communications, Graph processing, Outliers detection, Graph processing Structural graph clustering Big Graph Analysis Community detection Outliers detection hubs detection, hubs detection, Distributed computing, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI], [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG], Structural graph clustering, Graph clustering, Big graph, Hardware and Architecture, Distributed graph clustering, [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM], [INFO.INFO-DC]Computer Science [cs]/Distributed, Parallel, and Cluster Computing [cs.DC], SCAN, Software, Big Graph Analysis
Abstract: International audience; Graph clustering is one of the key techniques to understand structures that are presented in networks. In addition to clusters, bridges and outliers detection is also a critical task as it plays an important role in the analysis of networks. Recently, several graph clustering methods are developed and used in multiple application domains such as biological network analysis, recommendation systems and community detection. Most of these algorithms are based on the structural clustering algorithm. Yet, this kind of algorithm is based on the structural similarity. This latter requires to parse all graph’ edges in order to compute the structural similarity. However, the height needs of similarity computing make this algorithm more adequate for small graphs, without significant support to deal with large-scale networks. In this paper, we propose a novel distributed graph clustering algorithm based on structural graph clustering. The experimental results show the efficiency in terms of running time of the proposed algorithm in large networks compared to existing structural graph clustering methods.
Published: 2022

33. Vehicle routing with stochastic demands and partial reoptimization

Author: Alexandre M. Florio, Dominique Feillet, Marcus Poggi, Thibaut Vidal, Operations Planning Acc. & Control, École des Mines de Saint-Étienne (Mines Saint-Étienne MSE), Institut Mines-Télécom [Paris] (IMT), Laboratoire d'Informatique, de Modélisation et d'Optimisation des Systèmes (LIMOS), Ecole Nationale Supérieure des Mines de St Etienne (ENSM ST-ETIENNE)-Centre National de la Recherche Scientifique (CNRS)-Université Clermont Auvergne (UCA)-Institut national polytechnique Clermont Auvergne (INP Clermont Auvergne), Université Clermont Auvergne (UCA)-Université Clermont Auvergne (UCA), Pontifical Catholic University of Rio de Janeiro (PUC), and École Polytechnique de Montréal (EPM)
Subjects: 90B06, Optimization and Control (math.OC), recourse policies, FOS: Mathematics, Transportation, Branch-cut-and-price, [INFO.INFO-RO]Computer Science [cs]/Operations Research [cs.RO], Stochastic vehicle routing, switch policy, Mathematics - Optimization and Control, Civil and Structural Engineering
Abstract: We consider the vehicle routing problem with stochastic demands (VRPSD), a problem in which customer demands are known in distribution at the route planning stage and revealed during route execution upon arrival at each customer. A long-standing open question on the VRPSD concerns the benefits of allowing, during route execution, partial reordering of the planned customer visits. Given the practical importance of this question and the growing interest on the VRPSD under optimal restocking, we study the VRPSD under a recourse policy known as the switch policy. The switch policy is a canonical reoptimization policy that permits only pairs of successive customers to be reordered. We consider this policy jointly with optimal preventive restocking and introduce a branch-cut-and-price algorithm to compute optimal a priori routing plans. This algorithm features pricing routines where value functions represent the expected cost-to-go along planned routes for all possible states and reordering decisions. To ensure pricing tractability, we adopt a strategy that combines elementary pricing with completion bounds of varying complexity, and solve the pricing problem without relying on dominance rules. Our numerical experiments demonstrate the effectiveness of the algorithm for solving instances with up to 50 customers. Notably, they also give us new insights into the value of reoptimization. The switch policy enables significant cost savings over optimal restocking when the planned routes come from an algorithm built on a deterministic approximation of the data, an important scenario given the difficulty of finding optimal VRPSD solutions. The benefits are smaller when comparing optimal a priori VRPSD solutions obtained for both recourse policies. As it appears, further cost savings may require joint reordering and reassignment of customer visits among vehicles when the context permits., Comment: 28 pages
Published: 2022

34. STRONG SUSTAINABILITY ASPECTS IN THE IDEATION PROCESS: A PEDAGOGICAL EXPERIMENT

Author: Escobar, Melissa, Laforest, Valérie, Troussier, Nadège, Faucheu, Jenny, École des Mines de Saint-Étienne (Mines Saint-Étienne MSE), Institut Mines-Télécom [Paris] (IMT), Environnement, Ville, Société (EVS), École normale supérieure de Lyon (ENS de Lyon)-École des Mines de Saint-Étienne (Mines Saint-Étienne MSE), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Université Lumière - Lyon 2 (UL2)-Université Jean Moulin - Lyon 3 (UJML), Université de Lyon-Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Jean Monnet - Saint-Étienne (UJM)-École Nationale des Travaux Publics de l'État (ENTPE)-École nationale supérieure d'architecture de Lyon (ENSAL)-Centre National de la Recherche Scientifique (CNRS), Institut Henri Fayol (FAYOL-ENSMSE), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), Département Génie de l’environnement et des organisations (FAYOL-ENSMSE), Institut Henri Fayol-Ecole Nationale Supérieure des Mines de St Etienne (ENSM ST-ETIENNE), Centre de Recherches et d'Etudes Interdisciplinaires sur le Développement Durable (CREIDD), Institut Charles Delaunay (ICD), Université de Technologie de Troyes (UTT)-Centre National de la Recherche Scientifique (CNRS)-Université de Technologie de Troyes (UTT)-Centre National de la Recherche Scientifique (CNRS), Laboratoire Georges Friedel (LGF-ENSMSE), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Université de Lyon-Centre National de la Recherche Scientifique (CNRS), and ANR-20-CE10-0006,D-TechnoSS,Concevoir la technologie pour une soutenabilité forte(2020)
Subjects: Creativity, [SPI]Engineering Sciences [physics], Design education, Sustainability, Strong Sustainability
Abstract: International audience; The progress of science and technology has considerably increased the quality of life - especially the material standard of living - (e.g. disappearance of famines, increase in life expectancy) On the other hand, climate change, reduction of biodiversity, decrease of natural resources, and increase of environmental risks are some of the consequences of this human activities. Addressing these new challenges will require holistic comprehension and actionable approaches. The mitigation of these consequences requires effective responses in terms of transition. In this context, engineering and design students need time but also adapted curricula focused on sustainability and eco design concepts to support evolution of their skills, their knowledge and their culture. This article discusses the integration of a strong sustainability knowledge within the ideation process through a pedagogical experience, in order to develop new knowledge-based approaches, methodologies and tools
Published: 2023

35. FB15k-CVT: A Challenging Dataset for Knowledge Graph Embedding Models

Author: Iferroudjene, Mouloud, Charpenay, Victor, Zimmermann, Antoine, École des Mines de Saint-Étienne (Mines Saint-Étienne MSE), Institut Mines-Télécom [Paris] (IMT), Laboratoire d'Informatique, de Modélisation et d'Optimisation des Systèmes (LIMOS), Ecole Nationale Supérieure des Mines de St Etienne (ENSM ST-ETIENNE)-Centre National de la Recherche Scientifique (CNRS)-Université Clermont Auvergne (UCA)-Institut national polytechnique Clermont Auvergne (INP Clermont Auvergne), Université Clermont Auvergne (UCA)-Université Clermont Auvergne (UCA), Département Informatique et systèmes intelligents ( FAYOL-ENSMSE), Ecole Nationale Supérieure des Mines de St Etienne (ENSM ST-ETIENNE), Institut Henri Fayol (FAYOL-ENSMSE), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), and Courbon Software
Subjects: FB15K-237, Neurosymbolic AI, [INFO.INFO-WB]Computer Science [cs]/Web, [INFO]Computer Science [cs], Knowldge Graph Embeddings Models, Knowledge Graphs, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]
Abstract: International audience; Knowledge Graphs (KGs) are an essential component of neuro-symbolic AI. KG Embedding Models (KGEMs) are used to represent elements of a KG (its entities and relations) in a vector space, to enable efficient processing and reasoning over knowledge. Most KGEMs are evaluated against datasets derived from the Freebase KG: FB15k and FB15k-237. In this paper, we identify limitations in these datasets with respect to Compound Value Types (CVTs), which are nodes introduced in Freebase as a substitute for \uD835\uDC5B-ary relations. In FB15k and FB51k-237, CVTs have been removed, thereby eliminating valuable information. To evaluate whether KGEMs can learn semantically accurate representations of entities and relations in Freebase, we introduce here a new dataset named FB15k-CVT, which reintroduces the deleted CVT nodes. In a preliminary evaluation, we assess the limitations of baseline KGEMs (TransE, DistMult) in the presence of CVTs. The evaluation suggests that KGEMs based on tensor decomposition are more promising than translational models but, most of all, it calls for further experiments with KGEMs that can answer conjunctive queries or that preserve logical entailment.
Published: 2023

36. Enable Decentralised Semantic Content Negotiation through Equivalence Links

Author: Taghzouti, Yousouf, École des Mines de Saint-Étienne (Mines Saint-Étienne MSE), Institut Mines-Télécom [Paris] (IMT), Institut Henri Fayol (FAYOL-ENSMSE), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), Laboratoire d'Informatique, de Modélisation et d'Optimisation des Systèmes (LIMOS), Ecole Nationale Supérieure des Mines de St Etienne (ENSM ST-ETIENNE)-Centre National de la Recherche Scientifique (CNRS)-Université Clermont Auvergne (UCA)-Institut national polytechnique Clermont Auvergne (INP Clermont Auvergne), Université Clermont Auvergne (UCA)-Université Clermont Auvergne (UCA), Département Informatique et systèmes intelligents ( FAYOL-ENSMSE), and Ecole Nationale Supérieure des Mines de St Etienne (ENSM ST-ETIENNE)
Subjects: [INFO.INFO-WB]Computer Science [cs]/Web
Abstract: International audience; The Web is a decentralised system where servers can serve a set of URIs that identify resources. A resource may have one or more representations [2]. This encourages Content Negotiation (CN), the mechanism by which a client can request a resource representation that satisfies some constraints [1, Section 12]. In the SemanticWeb, resources are described using different vocabularies. HTTP provides the means to negotiate representations that have a required media type.Similarly, semantic validation languages (e.g. SHACL) could be used to define the constraints that knowledge graphs must satisfy. If a resource were identified by a single URI (unique names assumption), this would imply that all representations would be on one server. However, this is not possible on the currentWeb, because Web standards do not assume unique names and representations are distributed in different places. We propose an approach to perform content negotiation even when representations are distributed and present in multiple locations by using equivalence links, which involves on-the-fly SHACL shape validation.
Published: 2023

37. Optimality and Approximation Ratios of Demodulator Allocation Strategies in LoRa Multi-Gateway Networks

Author: Guitton, Alexandre, Kaneko, Megumi, Rachkidy, Nancy, Université Clermont Auvergne (UCA), Laboratoire d'Informatique, de Modélisation et d'Optimisation des Systèmes (LIMOS), Ecole Nationale Supérieure des Mines de St Etienne (ENSM ST-ETIENNE)-Centre National de la Recherche Scientifique (CNRS)-Université Clermont Auvergne (UCA)-Institut national polytechnique Clermont Auvergne (INP Clermont Auvergne), Université Clermont Auvergne (UCA)-Université Clermont Auvergne (UCA), AlGorithmes et Optimisation pour Réseaux Autonomes (AGORA), CITI Centre of Innovation in Telecommunications and Integration of services (CITI), Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Inria Lyon, Institut National de Recherche en Informatique et en Automatique (Inria), National Institute of Informatics (NII), Japanese French Laboratory for Informatics (JFLI), and National Institute of Informatics (NII)-The University of Tokyo (UTokyo)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)
Subjects: [INFO.INFO-NI]Computer Science [cs]/Networking and Internet Architecture [cs.NI], demodulator allocation, multi-gateway, LoRa, Internet of Things (IoT), LoRaWAN
Abstract: Long Range (LoRa) is a wireless modulation used to provide longrange connectivity to low-power devices of the Internet of Things (IoT). LoRa gateways use hardware chips called demodulators in order to demodulate concurrent frames on different channels or spreading factors. In this paper, we establish several theoretical results on the performance of fundamental demodulator allocating strategies. In the single gateway scenario, we first prove the optimality of the basic preemptive allocation strategy. Next, in the multi-gateway scenario, the greedy non-collaborative strategy, which is currently implemented in LoRa gateways, is shown to achieve a very large approximation ratio. As an alternative, we demonstrate that a preemptive non-collaborative strategy has an approximation ratio of 2, and furthermore, that a preemptive smartcollaborative strategy reaches an approximation ratio of 3/2, for two gateways. These seminal results imply that the current performance of multi-gateway LoRa deployments can be largely improved by the proposed collaborative demodulator allocation strategies.
Published: 2023

38. Multiobjective optimization with a quadratic surrogate-assisted CMA-ES

Author: Gharafi, Mohamed, Hansen, Nikolaus, Brockhoff, Dimo, Le Riche, Rodolphe, Randomized Optimisation (RANDOPT ), Centre de Mathématiques Appliquées - Ecole Polytechnique (CMAP), École polytechnique (X)-Centre National de la Recherche Scientifique (CNRS)-École polytechnique (X)-Centre National de la Recherche Scientifique (CNRS)-Inria Saclay - Ile de France, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Ecole Nationale Supérieure des Mines de St Etienne (ENSM ST-ETIENNE), Centre National de la Recherche Scientifique (CNRS), GECCO, Laboratoire d'Informatique, de Modélisation et d'Optimisation des Systèmes (LIMOS), Ecole Nationale Supérieure des Mines de St Etienne (ENSM ST-ETIENNE)-Université Clermont Auvergne [2017-2020] (UCA [2017-2020])-Centre National de la Recherche Scientifique (CNRS), and Université Clermont Auvergne [2017-2020] (UCA [2017-2020])
Subjects: multiobjective optimization CMA-ES evolution strategies surrogateassisted optimization quadratic metamodel, [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG], evolution strategies, multiobjective optimization, surrogateassisted optimization, CMA-ES, quadratic metamodel, [MATH.MATH-OC]Mathematics [math]/Optimization and Control [math.OC], [INFO.INFO-NE]Computer Science [cs]/Neural and Evolutionary Computing [cs.NE]
Abstract: International audience; We present a surrogate-assisted multiobjective optimization algorithm. The aggregation of the objectives relies on the Uncrowded Hypervolume Improvement (UHVI) which is partly replaced by a linear-quadratic surrogate that is integrated into the CMA-ES algorithm. Surrogating the UHVI poses two challenges. First, the UHVI is a dynamic function, changing with the empirical Pareto set. Second, it is a composite function, defined differently for dominated and nondominated points. The presented algorithm is thought to be used with expensive functions of moderate dimension (up to about 50) with a quadratic surrogate which is updated based on its ranking ability. We report numerical experiments which include tests on the COCO benchmark. The algorithm shows in particular linear convergence on the double sphere function with a convergence rate that is 6-20 times faster than without surrogate assistance.
Published: 2023

39. Welding fault detection and diagnosis using one-class SVM with distance substitution kernels and random convolutional kernel transform

Author: Melakhsou Abdallah Amine, Mireille Batton-Hubert, Nicolas Casoetto, École des Mines de Saint-Étienne (Mines Saint-Étienne MSE), Institut Mines-Télécom [Paris] (IMT), Laboratoire d'Informatique, de Modélisation et d'Optimisation des Systèmes (LIMOS), Ecole Nationale Supérieure des Mines de St Etienne (ENSM ST-ETIENNE)-Centre National de la Recherche Scientifique (CNRS)-Université Clermont Auvergne (UCA)-Institut national polytechnique Clermont Auvergne (INP Clermont Auvergne), Université Clermont Auvergne (UCA)-Université Clermont Auvergne (UCA), Institut Henri Fayol (FAYOL-ENSMSE), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), Département Génie mathématique et industriel (FAYOL-ENSMSE), Ecole Nationale Supérieure des Mines de St Etienne (ENSM ST-ETIENNE)-Institut Henri Fayol, and e.l.m. Leblanc SAS
Subjects: Time series anomaly detection Welding fault detection Welding fault diagnosis, Welding fault detection, Time series anomaly detection, [MATH]Mathematics [math], [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation, Welding fault diagnosis
Abstract: Welding defect detection is still often performed by the human visual inspection or with non destructive tests. These quality inspections methods can be time consuming and can have an important error rate. In this paper, we propose an approach for the detection of welding faults through the detection of abnormal subsequences of the welding voltage signal. The approach is based on the One-Class SVM with distance substitution kernels. The One Class-SVM has been used in many works for the detection of abnormal subsequences. However, often after transforming the subsequences into a set of features. Nevertheless, finding the relevant features for anomaly detection may be challenging. Dealing with the raw subsequences in distance-based approaches, on the other hand, are known to be effective and can generalize well to different problems but they often suffer from high computational cost, which may restrict their application, especially with the need of real time predictions in an industrial context. We show in this work that the One-Class SVM can be successfully used directly with the raw subsequences. This is achieved by employing distance substitution kernels. These class of kernels has not yet gained widespread adoption for time series anomaly detection. The results show that the approach is both accurate and fast, which makes it more suitable for real-time welding monitoring. We further propose an approach for automatic diagnosis of welding defects.
Published: 2023

40. Generic Blockchain on Generic Human Behavior

Author: Gritti, Clémentine, Hayek, Frédéric, Lafourcade, Pascal, University of Canterbury [Christchurch], Laboratoire d'Informatique, de Modélisation et d'Optimisation des Systèmes (LIMOS), Ecole Nationale Supérieure des Mines de St Etienne (ENSM ST-ETIENNE)-Centre National de la Recherche Scientifique (CNRS)-Université Clermont Auvergne (UCA)-Institut national polytechnique Clermont Auvergne (INP Clermont Auvergne), and Université Clermont Auvergne (UCA)-Université Clermont Auvergne (UCA)
Subjects: Blockchain, Consensus, [INFO]Computer Science [cs]
Abstract: International audience; Blockchain is a type of distributed ledger. A wide range of consensus algorithms exists to reach consensus in a decentralized manner. However, most of them trade energy consumption for a degree of openness. Blockchains are primarily used for tokens and cryptocurrencies. Often the process of minting new tokens depends on actionable real world behaviors. A difficulty persists in securely translating said behavior into a decentralized blockchain. We formalize the generic concept of Proof of Behavior (PoB), and use it to create a consensus mechanism for generic permissionless blockchains.
Published: 2023

41. Feasibility study on using house-tree-person drawings for automatic analysis of depression

Author: Zhang, Jie, Yu, Yaoxiang, Barra, Vincent, Ruan, Xiaoming, Chen, Yu, Cai, Bo, School of Computer Engineering, Nanyang Technological University [Singapour], Laboratoire d'Informatique, de Modélisation et d'Optimisation des Systèmes (LIMOS), Ecole Nationale Supérieure des Mines de St Etienne (ENSM ST-ETIENNE)-Université Clermont Auvergne [2017-2020] (UCA [2017-2020])-Centre National de la Recherche Scientifique (CNRS), and University of South Florida [Tampa] (USF)
Subjects: [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG], [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing
Published: 2023

42. Hybridation opérationnelle des logiques OWL2 et ASP pour améliorer l'expressivité déclarative

Author: Goblet, X, Rey, C, Collange, A, Jeolis Solutions, Laboratoire d'Informatique, de Modélisation et d'Optimisation des Systèmes (LIMOS), Ecole Nationale Supérieure des Mines de St Etienne (ENSM ST-ETIENNE)-Centre National de la Recherche Scientifique (CNRS)-Université Clermont Auvergne (UCA)-Institut national polytechnique Clermont Auvergne (INP Clermont Auvergne), Université Clermont Auvergne (UCA)-Université Clermont Auvergne (UCA), AFIA-Association Française pour l'Intelligence Artificielle, ICube-laboratoire des sciences de l'ingénieur, de l'informatique et de l'imagerie, Christelle Launois, and Catherine Roussey
Subjects: OWL2, Owlready Framework, ASP, Hybridation de langages logiques, Module Owlready, Système Clingo, Clingo System, Hybridization of logical languages, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]
Abstract: National audience; As part of an activity recommendation tool dedicated to therapeutic patient education, we proposed the ORALOoS solution combining OWL2 + SWRL, augmented with the Python Owlready module. The use of the imperative code makes it possible to overcome certain limitations of expressiveness, such as the absence of negation in the SWRL rules. However, it strongly counterbalances the declarative character of the approach allowed by OWL2. While preserving this characteristic, we present a solution to replace the SWRL rules and the imperative code by a program in Answer Set Programming. This idea is not new, but few studies have led to truly operational solutions in an industrial context. Our proposal is suggested in two steps : 1) use of the Hexlite solver which gives good results in terms of declarative expressiveness but remains difficult to operate with, and 2) development of a new operational library, hybridizing OWL2 and ASP with features similar to Hexlite but easy to use.; Dans le cadre d'un outil de recommandation d'activités dédié à l'éducation thérapeutique du patient, nous avons proposé la solution ORALOoS combinant OWL2 + SWRL, augmentée du module Python Owlready. L'usage de code impératif permet de pallier certaines limitations d'expressivité, comme l'absence de négation dans les règles SWRL. Cependant, il contrebalance fortement le caractère déclaratif de l'approche permis par OWL2. Tout en préservant cette caractéristique, nous présentons une solution pour remplacer règles SWRL et code impératif par un programme en Answer Set Programming. Cette idée n'est pas nouvelle mais peu de travaux ont abouti à des solutions réellement opérationnelles dans un contexte industriel. Notre proposition est abordée en deux étapes : 1) utilisation du solveur Hexlite qui donne de bons résultats en termes d'expressivité déclarative mais reste difficile à mettre en oeuvre, et 2) développement d'une nouvelle librairie opérationnelle, hybridant OWL2 et ASP avec des fonctionnalités similaires à Hexlite mais d'un usage facilité.
Published: 2023

43. Pour une interopérabilité sémantique des applications IoT sur les espaces européens des données

Author: Lefrançois, Maxime, École des Mines de Saint-Étienne (Mines Saint-Étienne MSE), Institut Mines-Télécom [Paris] (IMT), Laboratoire d'Informatique, de Modélisation et d'Optimisation des Systèmes (LIMOS), Ecole Nationale Supérieure des Mines de St Etienne (ENSM ST-ETIENNE)-Centre National de la Recherche Scientifique (CNRS)-Université Clermont Auvergne (UCA)-Institut national polytechnique Clermont Auvergne (INP Clermont Auvergne), Université Clermont Auvergne (UCA)-Université Clermont Auvergne (UCA), Institut Henri Fayol (FAYOL-ENSMSE), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), Département Informatique et systèmes intelligents ( FAYOL-ENSMSE), and Ecole Nationale Supérieure des Mines de St Etienne (ENSM ST-ETIENNE)
Subjects: [INFO]Computer Science [cs], [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]
Abstract: National audience; L'ontologie SAREF (Smart Applications REFerence Ontology) est à l'honneur de l'ETSI IoT Conférence 2023. Elle est développée à l'ETSI pour contribuer à la stratégie européenne en matière de données.Lors de l'ETSI IoT Conférence, qui se tient du 4 jusqu’au 6 juillet dans les locaux de l'Institut européen des normes de télécommunications (ETSI) à Sophia-Antipolis, plusieurs présentations porteront sur l'ontologie SAREF, qui est une contribution de l'ETSI à l'interopérabilité sémantique sur les espaces européens des données.
Published: 2023

44. Quelles sont les émissions de GES de la filière déchets ? Présentation des enjeux et des différents outils d’analyse environnementale

Author: Tanguy, Audrey, École des Mines de Saint-Étienne (Mines Saint-Étienne MSE), Institut Mines-Télécom [Paris] (IMT), Environnement, Ville, Société (EVS), École normale supérieure de Lyon (ENS de Lyon)-École des Mines de Saint-Étienne (Mines Saint-Étienne MSE), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Université Lumière - Lyon 2 (UL2)-Université Jean Moulin - Lyon 3 (UJML), Université de Lyon-Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Jean Monnet - Saint-Étienne (UJM)-École Nationale des Travaux Publics de l'État (ENTPE)-École nationale supérieure d'architecture de Lyon (ENSAL)-Centre National de la Recherche Scientifique (CNRS), Institut Henri Fayol (FAYOL-ENSMSE), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), Département Génie de l’environnement et des organisations (FAYOL-ENSMSE), Institut Henri Fayol-Ecole Nationale Supérieure des Mines de St Etienne (ENSM ST-ETIENNE), and Cercle des Femmes de Environnement
Subjects: [SDE]Environmental Sciences
Abstract: National audience
Published: 2023

45. A Survey on IoT Programming Platforms: A Business-Domain Experts Perspective

Author: hannou, Fatma-zohra, École des Mines de Saint-Étienne (Mines Saint-Étienne MSE), Institut Mines-Télécom [Paris] (IMT), Laboratoire d'Informatique, de Modélisation et d'Optimisation des Systèmes (LIMOS), Ecole Nationale Supérieure des Mines de St Etienne (ENSM ST-ETIENNE)-Centre National de la Recherche Scientifique (CNRS)-Université Clermont Auvergne (UCA)-Institut national polytechnique Clermont Auvergne (INP Clermont Auvergne), Université Clermont Auvergne (UCA)-Université Clermont Auvergne (UCA), Institut Henri Fayol (FAYOL-ENSMSE), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), Département Informatique et systèmes intelligents ( FAYOL-ENSMSE), Ecole Nationale Supérieure des Mines de St Etienne (ENSM ST-ETIENNE), ETSI, and ANR-19-CE23-0012,CoSWoT,Web Sémantique des Objets Contraints(2019)
Subjects: [INFO]Computer Science [cs]
Abstract: The presentation aims to overview the landscape of Internet of Things programming platforms intended for business domain experts interested in using IoT for the digital transformation of their businesses.Choosing an IoT programming platform relies on several factors, including interoperability, security, scalability, cost, or supported functionalities. Use case requirements are confronted with each platform's guarantees to study the feasibility of IoT system deployment. With the spectrum of automation possibilities, the choice of an IoT platform also depends on its accessibility to non-technical users. For this, the support and tools platforms dedicate to programmers are crucial. What would be the required technical knowledge for developing an application? What would the learning curve be? What is the size and health of the user community? What expressiveness will the end user benefit from with graphical interfaces or domain-specific languages with natural language-like syntax? The presentation tackles all these questions and formulates some decision-support insights.The presentation includes a quick background on IoT platform characteristics and domain-specific languages they expose for programmers. Generic and Domain dedicated IoT platforms are then presented, grouped by the programming approach they adopt: model-driven, mashups or end-user programming. The presentation focuses on two IoT application domains: building automation and smart agriculture. It ends with some insights for domain experts to make informed decisions about IoT platform choices, following their use case requirements.
Published: 2023

46. The ETSI STF 653 roadmap towards the consolidation and factorization of SAREF with ontology patterns

Author: Lefrançois, Maxime, École des Mines de Saint-Étienne (Mines Saint-Étienne MSE), Institut Mines-Télécom [Paris] (IMT), Laboratoire d'Informatique, de Modélisation et d'Optimisation des Systèmes (LIMOS), Ecole Nationale Supérieure des Mines de St Etienne (ENSM ST-ETIENNE)-Centre National de la Recherche Scientifique (CNRS)-Université Clermont Auvergne (UCA)-Institut national polytechnique Clermont Auvergne (INP Clermont Auvergne), Université Clermont Auvergne (UCA)-Université Clermont Auvergne (UCA), Institut Henri Fayol (FAYOL-ENSMSE), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), Département Informatique et systèmes intelligents ( FAYOL-ENSMSE), Ecole Nationale Supérieure des Mines de St Etienne (ENSM ST-ETIENNE), and ETSI
Subjects: SAREF, [INFO.INFO-WB]Computer Science [cs]/Web, IoT technologies, Ontologies, [INFO]Computer Science [cs], [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]
Abstract: This presentation provides an overview of the progress on Specialist Task Force 641 Task 2, and STF 653."The overall goal of STF 641 Task 2 and STF 653 is to homogenise and facilitate the use of SAREF and existing 11 SAREF domain mapping by:• SAREF revision based on harmonisation using common ontology patterns• SAREF portal automatization (tooling) for ontologies with common patterns"This presentation will be based on the description of STF 641 and 653, progress report of Milestone A of STF 653, Stable draft TR 103 781, and initial development towards the factorization of the SAREF suite of ontologies.
Published: 2023

47. About spatial interpolation using mixture distributions for predicting Energy Performance Certificate

Author: Grossouvre, Marc, Rullière, Didier, Villot, Jonathan, URBS, Département Génie mathématique et industriel (FAYOL-ENSMSE), Ecole Nationale Supérieure des Mines de St Etienne (ENSM ST-ETIENNE)-Institut Henri Fayol, École des Mines de Saint-Étienne (Mines Saint-Étienne MSE), Institut Mines-Télécom [Paris] (IMT), Environnement, Ville, Société (EVS), École normale supérieure de Lyon (ENS de Lyon)-École des Mines de Saint-Étienne (Mines Saint-Étienne MSE), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Université Lumière - Lyon 2 (UL2)-Université Jean Moulin - Lyon 3 (UJML), Université de Lyon-Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Jean Monnet - Saint-Étienne (UJM)-École Nationale des Travaux Publics de l'État (ENTPE)-École nationale supérieure d'architecture de Lyon (ENSAL)-Centre National de la Recherche Scientifique (CNRS), Institut Henri Fayol (FAYOL-ENSMSE), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), Département Génie de l’environnement et des organisations (FAYOL-ENSMSE), and Institut Henri Fayol-Ecole Nationale Supérieure des Mines de St Etienne (ENSM ST-ETIENNE)
Subjects: données surfaciques, transition énergétique, krigeage par blocs, change of support, areal data, [SDE.ES]Environmental Sciences/Environmental and Society, Processus multi- échelle, [SPI]Engineering Sciences [physics], energy transition, Multi-scale processes, régression de surface à points, changement d’échelle, block Kriging, area-to-point regression
Abstract: International audience; Planning the energy transition requires decision makers to have an in-depth knowledge about a given territory. To achieve this, data is collected from multiple sources, at multiple scales, with constraints such as privacy policies. Resulting data informs about given areas of space without a specific point location. Such is the case of Energy Performance Certificate (EPC). EPC databases are released under specific constraints: anonymization, geo-localization with postal address, missing details. This paper shows that learning the observed EPCs to predict missing ones can also be seen as a spatial interpolation problem. It presents a way to treat EPC as a geo-localized information and predict its value at building level. Kriging methodology is applied to random fields observed at random locations to find a Best Linear Unbiased Predictor (BLUP). This new model is referred to as Mixture Kriging. While the usual Gaussian setting is lost, we show that conditional mean, variance and covariance can be derived. This new model gives interesting results in EPC prediction at building level which is a prerequisite for decision maker to target renovation efforts. The specific case of a city in France is taken as an example. The presented model includes Mixture co-Kriging so that covariates can be used to improve the result. It is also suggested that Mixture Kriging can be usefully implemented to control uncertainty propagation. We present potential applications on simulated data.; Pour planifier la transition énergétique, les décideurs ont besoin d’une connaissance approfondie de leur territoire. Pour cela, des données sont collectées de sources multiples, à plusieurs échelles, avec des contraintes comme les politiques de confidentialité. De telles données fournissent des informations sur des zones spatiales mais sans localisation spécifique. C’est le cas du Diagnostic de Performance Energétique (DPE). Les bases de données des DPE réalisés sont publiées sous des contraintes spécifiques : anonymisation, géolocalisation avec adresse postale, détails manquants. Ce document montre que l’apprentissage des DPE observés pour prédire les DPE manquants peut être considéré comme un problème d’interpolation spatiale. Il présente une manière de traiter le DPE en tant qu’information géolocalisée et de prédire sa valeur au niveau du bâtiment. La méthodologie du krigeage est appliquée à des champs aléatoires observés à des emplacements aléatoires pour trouver le meilleur prédicteur linéaire non biaisé (BLUP). Ce nouveau modèle est appelé krigeage de mixtures. Bien que le cadre gaussien habituel soit perdu, nous montrons que la moyenne conditionnelle, la variance et la covariance peuvent être calculées. Ce nouveau modèle donne des résultats intéressants dans la prédiction du DPE au niveau du bâtiment, ce qui est une condition préalable pour que les décideurs ciblent les efforts de rénovation. Le cas spécifique d’une ville française est pris comme exemple. Le modèle présenté inclut également le co-krigeage de mixtures de sorte que les covariables puissent être utilisées pour améliorer le résultat. Il est également suggéré que le krigeage de mixtures puisse être utilement mis en oeuvre pour contrôler la propagation de l’incertitude. Nous présentons des applications en ce sens sur des données simulées.
Published: 2023

48. A survey on how network simulators serve reinforcement learning in wireless networks

Author: Ergun, Serap, Sammour, Ibrahim, Chalhoub, Gérard, Laboratoire d'Informatique, de Modélisation et d'Optimisation des Systèmes (LIMOS), Ecole Nationale Supérieure des Mines de St Etienne (ENSM ST-ETIENNE)-Université Clermont Auvergne [2017-2020] (UCA [2017-2020])-Centre National de la Recherche Scientifique (CNRS), and IDEX-ISITE initiative 16-IDEX-0001 (CAP 20-25).
Subjects: reinforcement learning, wireless networks, network simulators, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]
Abstract: International audience; Rapid adoption of mobile devices, coupled with the increase in prominence of mobile applications and services, resulted in unprecedented infrastructure requirements for mobile and wireless networks. To improve user experience, future 5G and wireless network systems evolve to support increased mobile traffic, real-time precision analysis, and adaptable network resource management. As mobile environments become more complex, heterogeneous, and evolving, these tasks become more difficult. In order to solve these problems, many researchers rely on reinforcement learning. The success of reinforcement learning stems from its support for new and powerful tools that solve problems. Nodes mobility, instability of wireless connections, the coexistence of multiple wireless technologies, and resource sharing among users are a few examples of what makes a wireless network a dynamic system. Learning, which is the main feature of reinforcement learning, enables wireless nodes to adapt to the dynamics of the system over time. For the learning to be efficient, it should be done over realistic and varied conditions. This is where network simulation tools can be useful. Network simulators are extensively used when it comes to studying wireless network protocols. They offer the advantage of scaling up scenarios at minimum cost and the ability to test many possible configurations quicker under a controlled environment. The main purpose of this survey is to show how network simulators help in developing reinforcement learning techniques in wireless networks. We emphasize how these tools can be used in the learning process and which problems they can solve. In the end, we discuss open issues related to this topic and highlight some best practice guidelines when it comes to mixing network simulators, reinforcement learning, and wireless protocols.
Published: 2023

49. DITAN: A deep-learning domain agnostic framework for Detection and Interpretation of Temporally-based multivariate ANomalies

Author: Giannoulis, Michail, Harris, Andrew, Barra, Vincent, Laboratoire d'Informatique, de Modélisation et d'Optimisation des Systèmes (LIMOS), Ecole Nationale Supérieure des Mines de St Etienne (ENSM ST-ETIENNE)-Centre National de la Recherche Scientifique (CNRS)-Université Clermont Auvergne (UCA)-Institut national polytechnique Clermont Auvergne (INP Clermont Auvergne), Université Clermont Auvergne (UCA)-Université Clermont Auvergne (UCA), Laboratoire Magmas et Volcans (LMV), Institut national des sciences de l'Univers (INSU - CNRS)-Institut de Recherche pour le Développement et la société-Centre National de la Recherche Scientifique (CNRS)-Université Clermont Auvergne (UCA)-Observatoire de Physique du Globe de Clermont-Ferrand (OPGC), Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Clermont Auvergne (UCA)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Clermont Auvergne (UCA), and Ecole Nationale Supérieure des Mines de St Etienne (ENSM ST-ETIENNE)-Université Clermont Auvergne [2017-2020] (UCA [2017-2020])-Centre National de la Recherche Scientifique (CNRS)
Subjects: [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG], [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing
Abstract: International audience
Published: 2023

50. Subexponential parameterized algorithms for cycle-hitting problems in contact and intersection graphs of segments

Author: Berthe, Gaétan, Bougeret, Marin, Gonçalves, Daniel, Raymond, Jean-Florent, Algorithmes, Graphes et Combinatoire (ALGCO), 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), Laboratoire d'Informatique, de Modélisation et d'Optimisation des Systèmes (LIMOS), Ecole Nationale Supérieure des Mines de St Etienne (ENSM ST-ETIENNE)-Centre National de la Recherche Scientifique (CNRS)-Université Clermont Auvergne (UCA)-Institut national polytechnique Clermont Auvergne (INP Clermont Auvergne), Université Clermont Auvergne (UCA)-Université Clermont Auvergne (UCA), ANR-21-CE48-0004,GRALMECO,Algorithmique des problèmes de couverture métriques dans les graphes(2021), and ANR-20-CE48-0008,ELIT,Un Parcours par les Limites de l'Efficacité(2020)
Subjects: Computational Geometry (cs.CG), FOS: Computer and information sciences, [INFO.INFO-DS]Computer Science [cs]/Data Structures and Algorithms [cs.DS], Computer Science - Data Structures and Algorithms, Computer Science - Computational Geometry, Data Structures and Algorithms (cs.DS)
Abstract: In this paper we investigate the existence of subexponential parameterized algorithms of three fundamental cycle-hitting problems in geometric graph classes. The considered problems, \textsc{Triangle Hitting} (TH), \textsc{Feedback Vertex Set} (FVS), and \textsc{Odd Cycle Transversal} (OCT) ask for the existence in a graph $G$ of a set $X$ of at most $k$ vertices such that $G-X$ is, respectively, triangle-free, acyclic, or bipartite. Such subexponential parameterized algorithms are known to exist in planar and even $H$-minor free graphs from bidimensionality theory [Demaine et al., JACM 2005], and there is a recent line of work lifting these results to geometric graph classes consisting of intersection of "fat" objects ([Grigoriev et al., FOCS 2022] and [Lokshtanov et al., SODA 2022]). In this paper we focus on "thin" objects by considering intersection graphs of segments in the plane with $d$ possible slopes ($d$-DIR graphs) and contact graphs of segments in the plane. Assuming the ETH, we rule out the existence of algorithms: - solving TH in time $2^{o(n)}$ in 2-DIR graphs; and - solving TH, FVS, and OCT in time $2^{o(\sqrt{n})}$ in $K_{2,2}$-free contact 2-DIR graphs. These results indicate that additional restrictions are necessary in order to obtain subexponential parameterized algorithms for %these problems. In this direction we provide: - a $2^{O(k^{3/4}\cdot \log k)}n^{O(1)}$-time algorithm for FVS in contact segment graphs; - a $2^{O(\sqrt d\cdot t^2 \log t\cdot k^{2/3}\log k)} n^{O(1)}$-time algorithm for TH in $K_{t,t}$-free $d$-DIR graphs; and - a $2^{O(k^{7/9}\log^{3/2}k)} n^{O(1)}$-time algorithm for TH in contact segment graphs.
Published: 2023

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