Academic literature on the topic 'Connectivité des graphes'
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Journal articles on the topic "Connectivité des graphes"
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CLAUZEL, Céline, Christophe EGGERT, Simon TARABON, Lili PASQUET, Gilles VUIDEL, Marion BAILLEUL, Claude MIAUD, and Claire GODET. "Analyser la connectivité de la trame turquoise : définition, caractérisation et enjeux opérationnels." Sciences Eaux & Territoires, no. 43 (October 16, 2023): 67–71. http://dx.doi.org/10.20870/revue-set.2023.43.7642.
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Revue Sciences Eaux & Territoires - Vient de paraître en ligneLa fragmentation du paysage se matérialise par une rupture de connexion au sein des réseaux écologiques. Le concept de trame verte et bleue est apparu comme un outil de protection et de restauration des continuités écologiques dans les territoires. De nouvelles trames écologiques ont récemment été proposées pour identifier d’autres discontinuités écologiques effectives. C’est notamment le cas de la trame turquoise associant la trame bleue et la partie de la trame verte en interaction fonctionnelle. La trame turquoise regroupe ainsi différents types d’habitats aquatiques et terrestres dont dépendent de nombreuses espèces d’amphibiens, d’odonates et autres invertébrés ou encore de chiroptères. Cette nouvelle trame bénéficie d’une attention croissante dans le monde opérationnel, alors même que sa définition et les méthodes de caractérisation ne sont pas encore stabilisées. Cet article propose de contribuer à une meilleure définition et compréhension de la trame turquoise. S’appuyant sur la méthode des graphes paysagers, aujourd’hui largement utilisée pour modéliser les réseaux écologiques et mesurer leur connectivité, le projet INTERFACE a permis le développement d’un protocole innovant de réseau multi-habitats pour tenir compte de l’hétérogénéité des habitats dans l’évaluation de la connectivité de la trame turquoise. Il permet ainsi d’aller au-delà de la délimitation d’une zone tampon autour des cours d’eau et d'identifier les zones fonctionnelles à préserver, les zones vulnérables et les points de conflits où il serait intéressant de restaurer des habitats aquatiques et/ou terrestres pour améliorer les connectivités.
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Durand-Dubief, Françoise, Gabriel Kocevar, Claudio Stamile, Salem Hannoun, François Cotton, and Dominique Sappey-Marinier. "Analyse de la connectivité structurelle cérébrale par la théorie des graphes : une nouvelle caractérisation des formes cliniques de sclérose en plaques." Revue Neurologique 173 (March 2017): S124. http://dx.doi.org/10.1016/j.neurol.2017.01.216.
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Chawki, M. B., A. Verger, E. Klesse, T. Witjas, J. P. Azulay, A. Eusebio, and E. Guedj. "Étude TEP cérébrale des troubles du contrôle des impulsions dans la maladie de Parkinson : approche de la connectivité métabolique par théorie des graphes." Médecine Nucléaire 42, no. 3 (May 2018): 137. http://dx.doi.org/10.1016/j.mednuc.2018.03.015.
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Prajapati, Rajeshri, Amit Parikh, and Pradeep Jha. "Exploring Novel Edge Connectivity in Graph Theory and its Impact on Eulerian Line Graphs." International Journal of Science and Research (IJSR) 12, no. 11 (November 5, 2023): 1515–19. http://dx.doi.org/10.21275/sr231120155230.
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Kulli, V. R. "ATOM BOND CONNECTIVITY E-BANHATTI INDICES." INTERNATIONAL JOURNAL OF MATHEMATICS AND COMPUTER RESEARCH 11, no. 01 (January 30, 2023): 3201–8. http://dx.doi.org/10.47191/ijmcr/v11i1.13.
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In this paper, we introduce the atom bond connectivity E-Banhatti index and the sum atom bond connectivity E-Banhatti index of a graph. Also we compute these newly defined atom bond connectivity E-Banhatti indices for wheel graphs, friendship graphs, chain silicate networks, honeycomb networks and nanotubes.
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Zhao, Kewen. "A simple proof of Whitney's Theorem on connectivity in graphs." Mathematica Bohemica 136, no. 1 (2011): 25–26. http://dx.doi.org/10.21136/mb.2011.141446.
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Boronina, Anna, Vladimir Maksimenko, and Alexander E. Hramov. "Convolutional Neural Network Outperforms Graph Neural Network on the Spatially Variant Graph Data." Mathematics 11, no. 11 (May 30, 2023): 2515. http://dx.doi.org/10.3390/math11112515.
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Applying machine learning algorithms to graph-structured data has garnered significant attention in recent years due to the prevalence of inherent graph structures in real-life datasets. However, the direct application of traditional deep learning algorithms, such as Convolutional Neural Networks (CNNs), is limited as they are designed for regular Euclidean data like 2D grids and 1D sequences. In contrast, graph-structured data are in a non-Euclidean form. Graph Neural Networks (GNNs) are specifically designed to handle non-Euclidean data and make predictions based on connectivity rather than spatial structure. Real-life graph data can be broadly categorized into two types: spatially-invariant graphs, where the link structure between nodes is independent of their spatial positions, and spatially-variant graphs, where node positions provide additional information about the graph’s properties. However, there is limited understanding of the effect of spatial variance on the performance of Graph Neural Networks. In this study, we aim to address this issue by comparing the performance of GNNs and CNNs on spatially-variant and spatially-invariant graph data. In the case of spatially-variant graphs, when represented as adjacency matrices, they can exhibit Euclidean-like spatial structure. Based on this distinction, we hypothesize that CNNs may outperform GNNs when working with spatially-variant graphs, while GNNs may excel on spatially-invariant graphs. To test this hypothesis, we compared the performance of CNNs and GNNs under two scenarios: (i) graphs in the training and test sets had the same connectivity pattern and spatial structure, and (ii) graphs in the training and test sets had the same connectivity pattern but different spatial structures. Our results confirmed that the presence of spatial structure in a graph allows for the effective use of CNNs, which may even outperform GNNs. Thus, our study contributes to the understanding of the effect of spatial graph structure on the performance of machine learning methods and allows for the selection of an appropriate algorithm based on the spatial properties of the real-life graph dataset.
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Yalaniak Supriya Butte, Ashwini. "Neighbour Degree Connectivity Indices of Graphs and Its Applications to the Octane Isomers." International Journal of Science and Research (IJSR) 12, no. 4 (April 5, 2023): 1892–96. http://dx.doi.org/10.21275/sr23716144709.
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Jiang, Huiqin, and Yongsheng Rao. "Connectivity Index in Vague Graphs with Application in Construction." Discrete Dynamics in Nature and Society 2022 (February 15, 2022): 1–15. http://dx.doi.org/10.1155/2022/9082693.
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The vague graph (VG), which has recently gained a place in the family of fuzzy graph (FG), has shown good capabilities in the face of problems that cannot be expressed by fuzzy graphs and interval-valued fuzzy graphs. Connectivity index (CI) in graphs is a fundamental issue in fuzzy graph theory that has wide applications in the real world. The previous definitions’ limitations in the connectivity of fuzzy graphs directed us to offer new classifications in vague graph. Hence, in this paper, we investigate connectivity index, average connectivity index, and Randic index in vague graphs with several examples. Also, one of the motives of this research is to introduce some special types of vertices such as vague connectivity enhancing vertex, vague connectivity reducing vertex, and vague connectivity neutral vertex with their properties. Finally, an application of connectivity index in the selected town for building hospital is presented.
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Oellermann, Ortrud R. "Major n-connected graphs." Journal of the Australian Mathematical Society. Series A. Pure Mathematics and Statistics 47, no. 1 (August 1989): 43–52. http://dx.doi.org/10.1017/s1446788700031189.
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AbstractAn induced subgraph H of connectivity (edge-connectivity) n in a graph G is a major n-connected (major n-edge-connected) subgraph of G if H contains no subgraph with connectivity (edge- connectivity) exceeding n and H has maximum order with respect to this property. An induced subgraph is a major (major edge-) subgraph if it is a major n-connected (major n-edge-connected) subgraph for some n. Let m be the maximum order among all major subgraphs of C. Then the major connectivity set K(G) of G is defined as the set of all n for which there exists a major n-connected subgraph of G having order m. The major edge-connectivity set is defined analogously. The connectivity and the elements of the major connectivity set of a graph are compared, as are the elements of the major connectivity set and the major edge-connectivity set of a graph. It is shown that every set S of nonnegative integers is the major connectivity set of some graph G. Further, it is shown that for each positive integer m exceeding every element of S, there exists a graph G such that every major k-connected subgraph of G, where k ∈ K(G), has order m. Moreover, upper and lower bounds on the order of such graphs G are established.
Dissertations / Theses on the topic "Connectivité des graphes"
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Kang, Haiyan. "Arêtes suppressibles, cycles et connectivité." Paris 11, 2010. http://www.theses.fr/2010PA112060.
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Soit G un graphe k-connexe et e = uv une arête de G. G/e nous noterons le graphe obtenu à partir de G en supprimant les sommets u, v et en ajoutant un nouveau sommet v_e tels que v_e est adjacent à tous les anciens voisins de u et v. Si G/e est encore k-connexe, e est appelé un bord de k-contractile. La première partie de la thèse étudie une propriété d'un bord contractile en k-connexe graphiques sans triangle. Soit G un graphe k-connexe, et soit e une arête de G. Soit GӨe désigner le graphe obtenu à partir de G par l'opération suivante: (1) supprimer e de G pour obtenir G-e; (2) pour tout sommet fin de e avec un degré k-1, disons x, x supprimer, puis ajouter des bordures entre toute paire de sommets non- adjacents dans N_ (G-e)(x). Si GӨe est k-connexe, e est dit être une arête suppressible de G. La deuxième partie de la thèse étudie la répartition des arêtes suppressibles dans les graphes 3-connexes ou des graphes 5-connexes. En outre, nous confirmons la conjecture Thomassen pour deux classes de graphes 3-connexes avec des limites de bords amovibles ou de descendre du cycle le plus long. La dernière partie de la thèse est consacrée à la cyclabilité prisme de graphiques. Le prisme de plus d’un graphe G est le produit cartésien GK_2 de la graphe G et K_2. Un graphe G est appelé hamiltonien prisme si le prisme de plus de G est hamiltonien. Nous disons qu'une série H V (G) de sommets est cyclable dans G s'il existe un cycle C de G contenant tous les sommets de H. Pour H V (G), on dit que H est cyclable prisme dans GK_2 si H ∪ H’ est cyclable dans GK_2 où H' est la copie de H. Nous prolongeons la suite Ozeki sur hamiltonicité prisme cyclabilité prisme de S. Il est également avancé pour les graphes sans griffe, la borne peut être réduite de 3 avec un expectionLet G be a k-connected graph and e=uv an edge of G. By G/e we denote the graph obtained from G by deleting the vertices u,v and adding a new vertex v_e such that v_e is adjacent to all the former neighbors of u and v. If G/e is still k-connected, then e is called a k-contractible edge. The first part of the thesis studies a property of a contractible edge in k-connected triangle-free graphs. Let G be a k-connected graph, and let e be an edge of G. Let GӨe denote the graph obtained from G by the following operation: (1) delete e from G to get G-e; (2) for any end vertex of e with degree k-1, say x, delete x, and then add edges between any pair of non-adjacent vertices in N_{G-e}(x). If GӨe is k-connected, then e is said to be a removable edge of G. The second part of the thesis investigates the distribution of removable edges in 3-connected graphs or 5-connected graphs. In addition, we confirm Thomassen’s conjecture for two classes of 3-connected graphs with bounds of removable edges on or off a longest cycle. The last part of the thesis is devoted to the prism cyclability of graphs. The prism over a graph G is the Cartesian product GK_2 of G with the complete graph K_2. G is said to be prism hamiltonian if GK_2 is hamiltonian. We say that a set H V(G) of vertices is cyclable in G if there is a cycle C in G containing all vertices of H. For H V(G), we say that H is prism cyclable in GK_2 if H∪H' where H' is the copy of H is cyclable in GK_2. We extend Ozeki’s result on prism hamiltonicity to prism cyclability of S. It is also argued for claw-free graphs, the bound can be reduced 3 with one expection
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Yang, Weihua. "Supereulerian graphs, Hamiltonicity of graphes and several extremal problems in graphs." Phd thesis, Université Paris Sud - Paris XI, 2013. http://tel.archives-ouvertes.fr/tel-00877793.
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In this thesis, we focus on the following topics: supereulerian graphs, hamiltonian line graphs, fault-tolerant Hamiltonian laceability of Cayley graphs generated by transposition trees, and several extremal problems on the (minimum and/or maximum) size of graphs under a given graph property. The thesis includes six chapters. The first one is to introduce definitions and summary the main results of the thesis, and in the last chapter we introduce the furture research of the thesis. The main studies in Chapters 2 - 5 are as follows. In Chapter 2, we explore conditions for a graph to be supereulerian.In Section 1 of Chapter 2, we characterize the graphs with minimum degree at least 2 and matching number at most 3. By using the characterization, we strengthen the result in [93] and we also address a conjecture in the paper.In Section 2 of Chapter 2, we prove that if $d(x)+d(y)\geq n-1-p(n)$ for any edge $xy\in E(G)$, then $G$ is collapsible except for several special graphs, where $p(n)=0$ for $n$ even and $p(n)=1$ for $n$ odd. As a corollary, a characterization for graphs satisfying $d(x)+d(y)\geq n-1-p(n)$ for any edge $xy\in E(G)$ to be supereulerian is obtained. This result extends the result in [21].In Section 3 of Chapter 2, we focus on a conjecture posed by Chen and Lai [Conjecture~8.6 of [33]] that every 3-edge connected and essentially 6-edge connected graph is collapsible. We find a kind of sufficient conditions for a 3-edge connected graph to be collapsible.In Chapter 3, we mainly consider the hamiltonicity of 3-connected line graphs.In the first section of Chapter 3, we give several conditions for a line graph to be hamiltonian, especially we show that every 3-connected, essentially 11-connected line graph is hamilton- connected which strengthens the result in [91].In the second section of Chapter 3, we show that every 3-connected, essentially 10-connected line graph is hamiltonian-connected.In the third section of Chapter 3, we show that 3-connected, essentially 4-connected line graph of a graph with at most 9 vertices of degree 3 is hamiltonian. Moreover, if $G$ has 10 vertices of degree 3 and its line graph is not hamiltonian, then $G$ can be contractible to the Petersen graph.In Chapter 4, we consider edge fault-tolerant hamiltonicity of Cayley graphs generated by transposition trees. We first show that for any $F\subseteq E(Cay(B:S_{n}))$, if $|F|\leq n-3$ and $n\geq4$, then there exists a hamiltonian path in $Cay(B:S_{n})-F$ between every pair of vertices which are in different partite sets. Furthermore, we strengthen the above result in the second section by showing that $Cay(S_n,B)-F$ is bipancyclic if $Cay(S_n,B)$ is not a star graph, $n\geq4$ and $|F|\leq n-3$.In Chapter 5, we consider several extremal problems on the size of graphs.In Section 1 of Chapter 5, we bounds the size of the subgraph induced by $m$ vertices of hypercubes. We show that a subgraph induced by $m$ (denote $m$ by $\sum\limits_{i=0}^ {s}2^{t_i}$, $t_0=[\log_2m]$ and $t_i= [\log_2({m-\sum\limits_{r=0}^{i-1}2 ^{t_r}})]$ for $i\geq1$) vertices of an $n$-cube (hypercube) has at most $\sum\limits_{i=0}^{s}t_i2^{t_i-1} +\sum\limits_{i=0}^{s} i\cdot2^{t_i}$ edges. As its applications, we determine the $m$-extra edge-connectivity of hypercubes for $m\leq2^{[\frac{n}2]}$ and $g$-extra edge-connectivity of the folded hypercube for $g\leq n$.In Section 2 of Chapter 5, we partially study the minimum size of graphs with a given minimum degree and a given edge degree. As an application, we characterize some kinds of minimumrestricted edge connected graphs.In Section 3 of Chapter 5, we consider the minimum size of graphs satisfying Ore-condition.
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Carboni, Lucrezia. "Graphes pour l’exploration des réseaux de neurones artificiels et de la connectivité cérébrale humaine." Electronic Thesis or Diss., Université Grenoble Alpes, 2023. http://www.theses.fr/2023GRALM060.
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L'objectif principal de cette thèse est d'explorer la connectivité cérébrale et celle des réseaux de neurones artificiels d'un point de vue de leur connectivité. Un modèle par graphes pour l'analyse de la connectivité structurelle et fonctionnelle a été largement étudié dans le contexte du cerveau humain mais, un tel cadre d'analyse manque encore pour l'analyse des systèmes artificiels. Avec l'objectif d'intégrer l'analyse de la connectivité dans les système artificiels, cette recherche se concentre sur deux axes principaux. Dans le premier axe, l'objectif principal est de déterminer une caractérisation de la signature saine de la connectivité fonctionnelle de repos du cerveau humain. Pour atteindre cet objectif, une nouvelle méthode est proposée, intégrant des statistiques de graphe traditionnelles et des outils de réduction de réseau, pour déterminer des modèles de connectivité sains. Ainsi, nous construisons une comparaison en paires de graphes et un classifieur pour identifier les états pathologiques et identifier les régions cérébrales perturbées par une pathologie. De plus, la généralisation et la robustesse de la méthode proposée ont été étudiées sur plusieurs bases de données et variations de la qualité des données. Le deuxième axe de recherche explore les avantages de l'intégration des études de la connectivité inspirée du cerveau aux réseaux de neurones artificiels (ANNs) dans la perspective du développement de systèmes artificiels plus robustes. Un problème majeur de robustesse dans les modèles d'ANN est représenté par l'oubli catastrophique qui apparaît lorsque le réseau oublie dramatiquement les tâches précédemment apprises lors de l'adaptation à de nouvelles tâches. Notre travail démontre que la modélisation par graphes offre un cadre simple et élégant pour étudier les ANNs, comparer différentes stratégies d'apprentissage et détecter des comportements nuisibles tels que l'oubli catastrophique. De plus, nous soulignons le potentiel d'une adaptation à de nouvelles tâches en contrôlant les graphes afin d'atténuer efficacement l'oubli catastrophique et jetant ainsi les bases de futures recherches et explorations dans ce domaineThe main objective of this thesis is to explore brain and artificial neural network connectivity from agraph-based perspective. While structural and functional connectivity analysis has been extensivelystudied in the context of the human brain, there is a lack of a similar analysis framework in artificialsystems.To address this gap, this research focuses on two main axes.In the first axis, the main objective is to determine a healthy signature characterization of the humanbrain resting state functional connectivity. To achieve this objective, a novel framework is proposed,integrating traditional graph statistics and network reduction tools, to determine healthy connectivitypatterns. Hence, we build a graph pair-wise comparison and a classifier to identify pathological statesand rank associated perturbed brain regions. Additionally, the generalization and robustness of theproposed framework were investigated across multiple datasets and variations in data quality.The second research axis explores the benefits of brain-inspired connectivity exploration of artificialneural networks (ANNs) in the future perspective of more robust artificial systems development. Amajor robustness issue in ANN models is represented by catastrophic forgetting when the networkdramatically forgets previously learned tasks when adapting to new ones. Our work demonstrates thatgraph modeling offers a simple and elegant framework for investigating ANNs, comparing differentlearning strategies, and detecting deleterious behaviors such as catastrophic forgetting.Moreover, we explore the potential of leveraging graph-based insights to effectively mitigatecatastrophic forgetting, laying a foundation for future research and explorations in this area
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Suprano, Ilaria. "Étude de la connectivité cérébrale par IRM fonctionnelle et de diffusion dans l’intelligence." Thesis, Lyon, 2019. http://www.theses.fr/2019LYSE1282.
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L'idée que l'intelligence s’appuie non seulement sur des régions spécifiques du cerveau, mais également sur des réseaux cérébraux efficaces s’est récemment affirmée. En effet, on pense que l'organisation du cerveau humain repose sur des réseaux complexes et dynamiques dans lesquels la communication entre les régions cérébrales garantit un transfert efficace d'informations. Ces concepts nous ont amené à explorer les bases neurales de l'intelligence en combinant des techniques avancées d'IRM et la théorie des graphes. D'un côté, les techniques avancées d'IRM, telles que l'IRM fonctionnelle au repos (IRMf-rs) et l'IRM par diffusion (IRMd), permettent d'explorer respectivement la connectivité cérébrale fonctionnelle et structurale, tandis que la théorie des graphes permettent la caractérisation des propriétés des réseaux à différentes échelles, grâce à des métriques globales et locales. L'objectif de cette thèse est de caractériser la topologie des réseaux cérébraux fonctionnels et structurels chez les enfants et les adultes avec un quotient intellectuel supérieur (HIQ) par rapport aux sujets de niveau standard (SIQ). Premièrement, nous avons concentré notre attention sur une population d’enfants présentant différentes caractéristiques cognitives. Deux profils HIQ, à savoir homogène (Hom-HIQ) et hétérogène HIQ (Het-HIQ), ont été définis sur la base d'observations cliniques et de sous-tests du quotient intellectuel (QI). En utilisant des techniques d’IRMf-rs, nous avons examiné la topologie du réseau fonctionnel par « l’indice de rupture de nœud ». Nous avons trouvé des différences topologiques significatives dans les propriétés d'intégration et de ségrégation des réseaux chez les enfants HIQ par rapport aux enfants SIQ, pour le graphe cérébral entier, pour chaque graphe hémisphérique et pour la connectivité homotopique. De plus, ces changements de topologie étaient plus prononcés dans le sous-groupe Het-HIQ. Enfin, nous avons trouvé des corrélations significatives entre les changements des métriques de graphes et le QI total et d’autres indices du QI. Ces résultats ont démontré pour la première fois que les deux profils HIQ sont liés à une organisation différente du substrat neuronal. Ensuite, la connectivité structurale du réseau cérébral, mesurée par IRMd chez l’ensemble des enfants HIQ, est significativement différente de celle des enfants SIQ. Nous avons également aussi de fortes corrélations entre la densité des réseaux cérébraux des enfants et leurs scores d'intelligence. De plus, plusieurs corrélations ont été trouvées entre les métriques de graphe d'intégration suggérant que les performances de l'intelligence peuvent être liées à une organisation homogène des réseaux. Ces résultats ont démontré que le substrat neuronal de l'intelligence repose sur une microarchitecture de la substance blanche de forte densité et sur une organisation homogène des réseaux. Cette population a finalement été étudiée par IRMf avec une tâche de mémorisation de mots. Des changements significatifs ont été observés entre les groupes HIQ et SIQ. Cette étude confirme notre hypothèse selon laquelle les deux profils HIQ sont caractérisés par une activité cérébrale différente, avec un effet plus prononcé chez les enfants Het-HIQ. Enfin, nous avons étudié la connectivité fonctionnelle et structurale dans une population d’adultes HIQ. Nous avons trouvé plusieurs corrélations entre les métriques de graphe et les autres indices du QI. De même que pour la population d’enfants, les capacités cognitives élevées des adultes sont corrélées à une organisation homogène des réseaux structurels et fonctionnels et une modularité réduite. En conclusion, on a démontré que la sensibilité des métriques de graphes basées sur des techniques 'IRM avancées et de connectivité, telles que l’IRMf-rs et l'IRMd, était très utile pour mieux caractériser les réseaux cérébraux des enfants et des adultes, ainsi que pour distinguer différents profils d'intelligence chez les enfantsThe idea that intelligence is embedded not only in specific brain regions, but also in efficient brain networks has grown up. Indeed, human brain organization is believed to rely on complex and dynamic networks in which the communication between cerebral regions guarantees an efficient transfer of information. These recent concepts have led us to explore the neural bases of intelligence using both advanced MRI techniques in combination with graph analysis. On one hand, advanced MRI techniques, such as resting-state functional MRI (rs-fMRI) and diffusion MRI (dMRI) allow the exploration of respectively the functional and the structural brain connectivity while on the other hand, graph theory models allow the characterization of brain networks properties at different scales, thanks to global and local metrics. The aim of this thesis is to characterize the topology of functional and structural brain networks in children and in adults with an intelligence quotient higher (HIQ) than standard levels (SIQ). First, we focused our attention on a children population with different cognitive characteristics. Two HIQ profiles, namely homogeneous (Hom-HIQ) and heterogeneous HIQ (Het-HIQ), have been defined based on clinical observations and Intelligence Quotient (IQ) sub-tests. Using resting-state fMRI techniques, we examined the functional network topology changes, estimating the "hub disruption index", in these two HIQ profiles. We found significant topological differences in the integration and segregation properties of brain networks in HIQ compared to SIQ children, for the whole brain graph, for each hemispheric graph, and for the homotopic connectivity. These brain networks changes resulted to be more pronounced in Het-HIQ subgroup. Finally, we found significant correlations between the graph networks’ changes and the full-scale IQ, as well as some intelligence subscales. These results demonstrated for the first time, that different HIQ profiles are related to a different neural substrate organization. Then, the structural brain network connectivity, measured by dMRI in all HIQ children, were significantly different than in SIQ children. Also, we found strong correlations between the children brain networks density and their intelligence scores. Furthermore, several correlations were found between integration graph metrics suggesting that intelligence performances are probably related to a homogeneous network organization. These findings demonstrated that intelligence neural substrate is based on a strong white matter microarchitecture of the major fiber-bundles and a well-balanced network organization between local and global scales. This children population was finally studied using a memory-word task of fMRI. Significant changes were observed between both HIQ and SIQ groups. This study confirms our hypothesis that both HIQ profiles are characterized by a different brain activity, with stronger evidences in Het-HIQ children. Finally, we investigated both functional and structural connectivity in a population of adults HIQ. We found several correlations between graph metrics and intelligence sub-scores. As well as for the children population, high cognitive abilities of adults seem to be related brain structural and functional networks organization with a decreased modularity. In conclusion, the sensitivity of graph metrics based on advanced MRI techniques, such as rs-fMRI and dMRI, was demonstrated to be very helpful to provide a better characterization of children and adult HIQ, and further, to distinguish different intelligence profiles in children
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Dai, Tianjiao. "Some vertex colouring problems and a generalisation of Hamilton-connectivity in graphs." Electronic Thesis or Diss., université Paris-Saclay, 2023. http://www.theses.fr/2023UPASG067.
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La décomposition des graphes fait référence au processus de décomposer un graphe complexe en composantes plus simples et plus petites, souvent dans le but d'analyser ou de résoudre des problèmes liés au graphe. Il s'agit d'un outil important pour représenter la structure globale et les propriétés d'une manière plus détaillée. Il est aussi également utile pour résoudre des problèmes impliquant la recherche de structures spécifiques dans un graphe. Il existe plusieurs types courants de techniques de décomposition de graphe largement utilisées en théorie des graphes et dans des domaines connexes, notamment la décomposition en arbres, la décomposition en blocs, la décomposition modulaire, la décomposition hiérarchique, etc. Cette thèse étudie deux types de décomposition de sommets d'un graphe : les colorations propres (décomposition en ensembles indépendants) et la Hamilton-connectivité (décomposition en chemins internement disjoints entre deux ensembles où les chemins couvrent tous les sommets du graphe)The decomposition of graphs refers to the process of breaking down a complex graph into simpler, smaller components, often with the goal of analysing or solving problems related to the graph. It is an important tool to display the global structure and properties in a more fine-grained manner, and also useful in solving problems that involve finding specific structures in a graph. There are several common types of graph decomposition techniques that are widely used in graph theory and related fields, including tree decomposition, block decomposition, modular decomposition, hierarchical decomposition, etc. This thesis studies two kinds of vertex decomposition of a graph: proper colourings (decomposition into independent sets) and Hamilton-connectivity (decomposition into internally-disjoint paths between two sets where the paths cover all the vertices of graphs)
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Gargouri, Fatma. "Etude de la connectivité fonctionnelle dans les pathologies de mouvement de Parkinson et de Huntington en utilisant l’approche par graine et la théorie des graphes." Thesis, Paris 6, 2017. http://www.theses.fr/2017PA066487/document.
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L’imagerie par résonance magnétique fonctionnelle permet d’explorer l’activité neuronale en utilisant un contraste endogène appelé BOLD. Il a été montré que les fluctuations du signal BOLD au repos corrélaient dans des régions cérébrales distantes. C’est la connectivité fonctionnelle. Elle représente l’activité spontanée du cerveau et elle est mesurée par l’IRMf au repos. Notre projet de recherche a donc combiné un aspect méthodologique et deux applications dans le domaine des pathologies du mouvement. Nous avons étudié les stratégies de prétraitement des données. L'objectif était d'étudier l'influence du type de prétraitement ainsi que leur ordre d'application sur l'optimisation de la topologie des réseaux cérébraux. Nous avons comparé 12 stratégies différentes de prétraitement. Dans ces stratégies nous avons appliqué les techniques standards avec un ordre d'application différent. Les deux études suivantes ont utilisé l'IRMf au repos pour étudier la physiopathologie de deux pathologies du mouvement : la maladie de Huntington et la maladie de Parkinson. Dans ces pathologies, nous nous sommes centrés sur l'étude des réseaux cérébraux grâce à l'étude de la connectivité fonctionnelle. Nous avons déterminé si l'IRMf au repos et les mesures de la théorie des graphes permettaient d'identifier des biomarqueurs robustes de l'évolution de la maladie de Huntington dans une étude longitudinale. Ensuite, nous avons étudié le rôle des noyaux cholinergiques du cerveau basal antérieur et de leurs connexions dans la survenue des troubles cognitifs présentés par les patients atteints de maladie de Parkinson. L'approche par graine est une méthode adaptée à ce type de questionFunctional magnetic resonance imaging (fMRI) is a technique that allows exploring neuronal activity using an endogenous contrast based on the oxygenation level of hemoglobin. This contrast is called BOLD (Blood oxygenated Level Dependent). It has been shown that fluctuations in the BOLD signal at rest, correlated in distant brain regions, defining long-distance brain functional networks. This is called functional connectivity. The latter represents the spontaneous activity of the brain and it is measured by fMRI at rest. Our research project has therefore combined a methodological aspect and two applications in the field of movement pathologies. In the first part of our project we studied data preprocessing strategies. The objective was to study the influence of the preprocessing steps and their order of application on the brain networks’ topology. We compared 12 different pretreatment strategies. In these strategies we applied the standard and most used techniques but with a different order of application. The following two studies used resting-state fMRI to study: Huntington's disease and Parkinson's disease. In these pathologies, we focused on the study of the brain networks addressed through the study of functional connectivity. We determined whether resting-state fMRI and graph theory measures were able to identify robust biomarkers of Huntington's disease progression in a longitudinal study. In the second study, we investigated the role of cholinergic basal nuclei of the forebrain and their connections in the onset of cognitive problems presented in Parkinson's disease. The seed-based analysis is a suitable method for this type of question
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Oujamaa, Lydia. "Evolution topologique des hubs dans l'état de conscience altérée post-traumatique : un marqueur de récupération fonctionnelle." Thesis, Université Grenoble Alpes, 2020. http://www.theses.fr/2020GRALS013.
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Ce travail doctoral s’inscrit dans le champ de la recherche translationnelle. Nous avonsvoulu explorer la plasticité cérébrale post-lésionnelle qui sous-tend la restauration de la conscience après un coma traumatique. L’étude de la connectivité fonctionnelle de repos, c’est à dire de la corrélation temporelle du signal BOLD (blood oxygenationlevel dependent) entre régions cérébrales, a été appliquée à une cohorte de 36 patients traumatisés crâniens graves sortant de réanimation. A cette date, les patients pouvaient se trouver en état de conscience altérée ou être conscients. Nous avons réalisé une étude transversale et longitudinale : une 1ère IRM fonctionnelle en condition de veille de repos était réalisée à la sortie des soins intensifs et une seconde après un séjour de un moisen rééducation post-réanimation. Ainsi, à l’aide de la méthode des graphes, nous avons exploré l’intérêt diagnostique et pronostique de la connectivité fonctionnelle lors de la réémergence de la conscience après coma traumatique.Nous avons centré notre analyse sur un index de perturbation des hubs qui traduitla redistribution des connexions fonctionnelles dans le graphe. Les hubs du réseau cérébral,qui physiologiquement concentrent le plus de connexions, ont été caractérisésavec plusieurs métriques d’intégration, de ségrégation et de centralité dans le transfertd’information.Nos résultats suggèrent qu’une perturbation de la topologie des hubs fonctionnels estobjectivement "cartographiable" et qu’elle est corrélée à l’évolution neurologique cliniqueaprès agression cérébrale. En effet, notre étude a montré que, chez le traumatisé crâniengrave adulte, ce marqueur de perturbation fonctionnelle du réseau cérébral est sensible,dans une analyse de groupe, à l’état de conscience (patients conscients vs en état deconscience altérée) et à sa restauration au cours du temps. L’index de perturbation deshubs est également sensible à une autre dimension clinique : la prédiction du handicap neurologique à 6 mois post-coma.La computation des données de connectivité en une méta-donnée, l’index de perturbationdes hubs de l’ensemble du réseau cérébral, permet d’aller plus loin qu’un modèle descriptif de la plasticité cérébrale après coma (d’altération ou de restitution de connectivité dans un ou plusieurs réseaux). Ainsi, la restitution de la capacité du cerveau à traiterde l’information locale dans les hubs fonctionnels serait nécessaire à la ré-émergence de la conscience après coma traumatique. Ce résultat est original car dans la littérature actuelle, basée sur les théories de l’espace de travail global et de l’intégration de l’information,l’atteinte traumatique cérébrale est modélisée comme une altération de laconnectivité à longue distance et donc de l’intégration fonctionnelle.Cette étude pilote était un pré-requis pour évaluer à l’avenir cet index de perturbation fonctionnelle cérébrale à l’échelle individuelle et objectiver la réponse thérapeutique(psychostimulants, électrostimulation cérébrale....) de patients en état de conscience altéréeThis work takes part in the field of translational research. Our aim was to explore thepost-lesional brain plasticity necessary to recover consciousness after a traumatic coma.The study of resting state functional connectivity, meaning the temporal correlation ofBOLD signal (blood oxygenation level dependent) between remote cerebral areas, wasapplied to severe traumatic brain injured (sTBI) patients.Using graph method, we explored the diagnosis and prognosis value of resting statefunctional connectivity during recovery of consciousness after a traumatic coma.Thirty six sTBI patients were studied in a cross sectional and a longitudinal design.We recorded a resting state functional MRI sequence while sTBI patients were eitherconscious or in altered state of consciousness when discharged from intensive care unit(ICU). A second fMRI was recorded after one month spent in a post-ICU rehabilitationunit.Our analysis focused on a hub disruption index (HDI) which expresses the reallocationof functional connections inside the graph. In the brain network, the hubs, which are definedas highly connected to the brain network in healthy subjects, have been characterizedwith integration, segregation and centrality metrics for information transfer.Our results suggest that the topological disruption of functional hubs is an objectivemapping of the brain network changes that correlates with post-TBI neurological recovery.Indeed, in our group analysis, the hub disruption index of the post TBI brainnetwork was sensitive to the state of consciousness and to its recovery during a onemonth follow-up. This index was also relevant to predict the level of disability 6 monthsafter injury.The computation of connectivity data in a metadata, the hub disruption index ofthe brain network, enhances the classical approach describing the post-traumatic brainplasticity as a loss and recovery of connectivity in one or several cortical networks. Therecovery of the brain network ability to compute local information in the functionalhubs could be necessary to recover consciousness after a traumatic coma. This resultis original as the recent litterature, based on the information integration theory andthe global workspace theory of consciousness, is considering severe TBI as a long rangeconnectivity disruption inducing a functional integration impairment.This pilot study was necessary prior to the assessment of the HDI on a single-subjectlevel and to quantifie the response of brain injured patients with disorder of consciousnessto several therapeutic options (psychostimulant drugs, electrical stimulation..)
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König, Jean-Claude. "Les réseaux d'interconnexion et les algorithmes distribués." Paris 11, 1987. http://www.theses.fr/1987PA112069.
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Cette thèse comprend deux parties. La première concerne les réseaux d'interconnexion et en particulier leur résistance aux pannes. Le premier chapitre traite d'extension de réseaux; on construit des réseaux de connexité et de degré maximum donnés en ajoutant des sommets p par p par p ceci avec un nombre minimum de remaillages. Dans le second chapitre on étudie la vulnérabilité des réseaux par bus ce qui nous conduit à étudier diverses notions de connexité dans les hypergraphes uniformes. La deuxième partie est consacrée à l'algorithme, distribuée et particulièrement à tout ce qui concerne les problèmes de messagerie (diffusion, routage). Le chapitre 3 traite de la diffusion d'information ou de requêtes dans un réseau distribué. On définit un nouvel algorithme : permettant de construire un arbre couvrant et on l'applique au problème de l'on mutuelle. Nous utilisons des méthodes de contrôle des transferts de connaissance ainsi que des techniques de synchronisation et de filtrage. Le chapitre 4 présente un «méta-algorithme» distribué basé sur la notion de phases. De plus on précise le rôle et l’importance de la topologie du réseau dans l'algorithmique distribuée. Dans ces deux derniers chapitres on détermine la complexité en nombre de messages et en temps des algorithmes. Enfin nous donnons en annexe un algorithme d'ordonnancement pour le calcul parallèle qui est optimal si le graphe de précédence des tâches est de type "2-steps' (élimination de Gauss dans une matrice dense)This thesis contains two parts. Ln the first one we study interconnection networks and in particular their fault tolerance. The first chapter deals with the extensions of networks. We construct networks with given connectivity and maximum degree by adding the vertices p by p. In such a way that the minimum number possible of links is deleted. Ln chapter 2 we study the vulnerability of bus networks; this leads us to study various notions of connectivity in uniform hypergraphs. The second part concerns distributed algorithms, in particular problems of broadcasting and routing. Chapter 3 deals with the problem of broadcasting information or requests in a distributed net work. We give a new algorithm to construct a spanning tree and apply it to the problem of mutual exclusion. We use methods of control knowledge transfers and also synchronization and filtering methods. Ln chapter 4 we present a "meta-algorithm" based on the notion of phases. Furthermore we specify the use and the importance of the network topology in the distributed computing. Ln these two chapters we determine the complexity in number or messages and time of the proposed algorithms. Finally we give in the appendix a scheduling algorithm for parallel computing which is optimal for the 2-sceps precedence graph (Gaussian elimination in dense matrices)
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Cattai, Tiziana. "Leveraging brain connectivity networks to detect mental states during motor imagery." Electronic Thesis or Diss., Sorbonne université, 2021. http://www.theses.fr/2021SORUS081.
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Le cerveau est un réseau complexe et nous savons que les mécanismes de synchronisation et de désynchronisation sont essentiels pour effectuer des taches motrices et cognitives. De nos jours, les interactions fonctionnelles cérébrales sont étudiées dans des applications d'interface cerveau-ordinateur (BCI) avec de plus en plus d'intérêt. Cela pourrait avoir un fort impact sur les systèmes BCI, généralement bases sur des caractéristiques univariées qui caractérisent séparément les activités régionales du cerveau. En effet, les fonctionnalités de connectivité cérébrale peuvent être utilisées pour développer des BCI alternatifs dans le but d'améliorer les performances et d'\'e9tendre leur applicabilité dans la vie r\'e9elle. L'ambition de cette thèse est l'étude des réseaux de connectivité fonctionnelle du cerveau lors de taches BCI basées sur l'imagerie motrice (IM). Il vise à identifier le fonctionnement cérébral complexe, les processus de réorganisation et les dynamiques variant dans le temps à la fois au niveau du groupe et de l'individu. Cette thèse présente différents développements qui enrichissent séquentiellement un modèle initialement simple afin d'obtenir une méthode robuste pour l'étude des réseaux de connectivité fonctionnelle. Les résultats expérimentaux sur des données EEG simulées et réelles enregistrés pendant les taches BCI prouvent que notre méthode proposée explique bien le comportement variegate des données EEG cérébrales. Plus précisément, il fournit une caractérisation des mécanismes fonctionnels du cerveau au niveau du groupe, ainsi qu'une mesure de la séparabilité des conditions mentales au niveau individuel. Nous présentons également une procédure de réduction du bruit de graphe pour filtrer les données qui préservent simultanément la structure de connectivité du graphe et améliorent le rapport signal sur bruit. Puisque l'utilisation d'un système BCI nécessite une interaction dynamique entre l'utilisateur et la machine, nous proposons enfin une méthode pour capturer l'évolution des données variant dans le temps. Essentiellement, cette thèse présente un nouveau cadre pour saisir la complexité de la connectivité fonctionnelle des graphes lors de tâches cognitivesThe brain is a complex network and we know that inter-areal synchronization and de-synchronization mechanisms are crucial to perform motor and cognitive tasks. Nowadays, brain functional interactions are studied in brain-computer interface BCI) applications with more and more interest. This might have strong impact on BCI systems, typically based on univariate features which separately characterize brain regional activities. Indeed, brain connectivity features can be used to develop alternative BCIs in an effort to improve performance and to extend their real-life applicability. The ambition of this thesis is the investigation of brain functional connectivity networks during motor imagery (MI)-based BCI tasks. It aims to identify complex brain functioning, re-organization processes and time-varying dynamics, at both group and individual level. This thesis presents different developments that sequentially enrich an initially simple model in order to obtain a robust method for the study of functional connectivity networks. Experimental results on simulated and real EEG data recorded during BCI tasks prove that our proposed method well explains the variegate behaviour of brain EEG data. Specifically, it provides a characterization of brain functional mechanisms at group level, together with a measure of the separability of mental conditions at individual level. We also present a graph denoising procedure to filter data which simultaneously preserve the graph connectivity structure and enhance the signal-to-noise ratio. Since the use of a BCI system requires a dynamic interaction between user and machine, we finally propose a method to capture the evolution of time-varying data. In essence, this thesis presents a novel framework to grasp the complexity of graph functional connectivity during cognitive tasks
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Termenon, Conde Maite. "Analyse par graphes de la connectivité fonctionnelle de repos par IRM : vers de nouveaux biomarqueurs de la récupération fonctionnelle dans l'AVC." Thesis, Université Grenoble Alpes (ComUE), 2016. http://www.theses.fr/2016GREAS023/document.
Full textBooks on the topic "Connectivité des graphes"
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West, Douglas Brent. Introduction to graph theory. Upper Saddle River, NJ: Prentice Hall, 1996.
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Li, Xueliang, and Yaping Mao. Generalized Connectivity of Graphs. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-33828-6.
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Li, Xueliang, Colton Magnant, and Zhongmei Qin. Properly Colored Connectivity of Graphs. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-89617-5.
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Nagamochi, Hiroshi. Algorithmic aspects of graph connectivity. New York: Cambridge University Press, 2008.
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Toshihide, Ibaraki, ed. Algorithmic aspects of graph connectivity. New York: Cambridge University Press, 2008.
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Molitierno, Jason J. Applications of combinatorial matrix theory to Laplacian matrices of graphs. Boca Raton: CRC Press, 2012.
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Molitierno, Jason J. Applications of combinatorial matrix theory to Laplacian matrices of graphs. Boca Raton: CRC Press, 2012.
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Introduction to graph theory. 2nd ed. Upper Saddle River, N.J: Prentice Hall, 2001.
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Molitierno, Jason J. Applications of Combinatorial Matrix Theory to Laplacian Matrices of Graphs. Taylor & Francis Group, 2016.
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Molitierno, Jason J. Applications of Combinatorial Matrix Theory to Laplacian Matrices of Graphs. Taylor & Francis Group, 2012.
Find full textBook chapters on the topic "Connectivité des graphes"
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Chartrand, Gary, Heather Jordon, Vincent Vatter, and Ping Zhang. "Connectivity." In Graphs & Digraphs, 81–102. 7th ed. Boca Raton: Chapman and Hall/CRC, 2023. http://dx.doi.org/10.1201/9781003461289-4.
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Jungnickel, Dieter. "Connectivity." In Graphs, Networks and Algorithms, 331–53. Berlin, Heidelberg: Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/978-3-662-03822-2_11.
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Diestel, Reinhard. "Connectivity." In Graph Theory, 59–87. Berlin, Heidelberg: Springer Berlin Heidelberg, 2017. http://dx.doi.org/10.1007/978-3-662-53622-3_3.
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Diestel, Reinhard. "Connectivity." In Graph Theory, 59–86. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/978-3-642-14279-6_3.
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Aldous, Joan M., and Robin J. Wilson. "Paths and Connectivity." In Graphs and Applications, 216–41. London: Springer London, 2000. http://dx.doi.org/10.1007/978-1-4471-0467-4_10.
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Li, Xueliang, Colton Magnant, and Zhongmei Qin. "Directed Graphs." In Properly Colored Connectivity of Graphs, 97–102. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-89617-5_10.
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Li, Xueliang, Colton Magnant, and Zhongmei Qin. "Random Graphs." In Properly Colored Connectivity of Graphs, 63–72. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-89617-5_7.
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Li, Xueliang, Colton Magnant, and Zhongmei Qin. "Connectivity Conditions." In Properly Colored Connectivity of Graphs, 15–22. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-89617-5_3.
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Li, Xueliang, and Yaping Mao. "Introduction." In Generalized Connectivity of Graphs, 1–13. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-33828-6_1.
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Li, Xueliang, and Yaping Mao. "Results for Some Graph Classes." In Generalized Connectivity of Graphs, 15–29. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-33828-6_2.
Full textConference papers on the topic "Connectivité des graphes"
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Namouz, Essam Z., and Joshua D. Summers. "Comparison of Graph Generation Methods for Structural Complexity Based Assembly Time Estimation." In ASME 2013 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/detc2013-12300.
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This paper compares two different methods of graph generation for input into the complexity connectivity method to estimate the assembly time of a product. The complexity connectivity method builds predictive models for assembly time based on twenty-nine complexity metrics applied to the product graphs. Previously the part connection graph was manually created, but recently the Assembly Mate Method and the Interference Detection Method have introduced new automated tools for creating the part connectivity graphs. These graph generation methods are compared on their ability to predict the assembly time of multiple products. For this research, eleven consumers products are used to train an artificial neural network and three products are reserved for testing. The results indicate that both the Assembly Mate Method and the Interference Detection Method can create connectivity graphs that predict the assembly time of a product to within 45% of the target time. The Interference Detection Method showed less variability than the Assembly Mate Method in the time estimations. The Assembly Mate Method is limited to only SolidWorks assembly files, while the Interference Detection Method is more flexible and can operate on different file formats including IGES, STEP, and Parasolid. Overall, both of the graph generation methods provide a suitable automated tool to form the connectivity graph, but the Interference Detection Method provides less variance in predicting the assembly time and is more flexible in terms of file types that can be used.
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Jongsma, T. J., and W. Zhang. "An Efficient Algorithm for Finding Optimum Code Under the Condition of Incident Degree." In ASME 1992 Design Technical Conferences. American Society of Mechanical Engineers, 1992. http://dx.doi.org/10.1115/detc1992-0409.
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Abstract This paper deals with the identification of kinematic chains. A kinematic chain can be represented by a weighed graph. The identification of kinematic chains is thereby transformed into the isomorphism problem of graph. When a computer program has to detect isomorphism between two graphs, the first step is to set up the corresponding connectivity matrices for each graph, which are adjacency matrices when considering adjacent vertices and the weighed edges between them. Because these adjacency matrices are dependent of the initial labelling, one can not conclude that the graphs differ when these matrices differ. The isomorphism problem needs an algorithm which is independent of the initial labelling. This paper provides such an algorithm.
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Hahn, Elad, and Offer Shai. "The Unique Engineering Properties of Assur Groups/Graphs, Assur Kinematic Chains, Baranov Trusses and Parallel Robots." In ASME 2016 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/detc2016-59135.
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Modular topological structures, commonly known as Assur groups, have been an important subject of research in machine theory over the past several decades. In this paper, some unique engineering properties which appear in this type of structures and only in them are exposed. The concept of Assur groups is reformulated in terms of graphs and named Assur Graphs (AGs). The graph representation enables to present the inter-connectivity between all the elements of the AG, which is the fundamental characteristic from which all its unique properties derive. This inter-connectivity leads to unique properties in three main engineering aspects of structures: kinematics, statics and singularity positions. These properties can be exploited for better analysis and synthesis of structures such as mechanisms, robots and trusses.
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Duarte Jr., Elias Procópio, and Andréa Weber. "Simulation of a Distributed Connectivity Algorithm for General Topology Networks." In Workshop de Testes e Tolerância a Falhas. Sociedade Brasileira de Computação - SBC, 2002. http://dx.doi.org/10.5753/wtf.2002.23409.
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The Distributed Network Connectivity algorithm allows every node in a general topology network to determine to which portions of the network it is connected, and which portions are unreachable. The algorithm consists of three phases: test, dissemination, and connectivity computation. During the testing phase each fault-free node tests all its neighbors at each testing interval. Upon the detection of a new fault event, the tester starts the dissemination phase, in which a reliable broadcast algorithm is employed to inform the other connected nodes about the event. At any time, any working node may run the third phase, in which a graph connectivity algorithm shows the complete network connectivity. Extensive simulation results are presented, considering various topologies such as the hypercube and random graphs. Results are compared to those of other algorithms.
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Hooshmand, Amir, and Matthew I. Campbell. "Tensegrity Form-Finding Using Generative Design Synthesis Approach." In ASME 2015 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/detc2015-47954.
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The aim of this research is to produce large irregular tensegrity structures using a generative design synthesis approach. Unlike most of the form-finding methods, the approach does not require the description of the connectivity of the tensegrity structures to define the shape of the tensegrities. It uses graphs to represent the tensegrity structures, which allows a very fast generation of stable tensegrity solutions for a given design problem. The graph grammar interpreter, GraphSynth, is used to carry out graph transformations, which define different configurations for a given design problem. After generating the graphs, they are transformed into meaningful 3D shapes. The effectiveness and robustness of the proposed method is checked by solving a variety of test problems.
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Jafarpour, Maryam, Mohammad Shekaramiz, Abolfazl Javan, and Ali Moeini. "Building Graphs with Maximum Connectivity." In 2020 Intermountain Engineering, Technology and Computing (IETC). IEEE, 2020. http://dx.doi.org/10.1109/ietc47856.2020.9249130.
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Charrier, Tristan, Arthur Queffelec, Ocan Sankur, and François Schwarzentruber. "Reachability and Coverage Planning for Connected Agents." In Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. California: International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/21.
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Motivated by the increasing appeal of robots in information-gathering missions, we study multi-agent path planning problems in which the agents must remain interconnected. We model an area by a topological graph specifying the movement and the connectivity constraints of the agents. We study the theoretical complexity of the reachability and the coverage problems of a fleet of connected agents on various classes of topological graphs. We establish the complexity of these problems on known classes, and introduce a new class called sight-moveable graphs which admit efficient algorithms.
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You, Lantao, Yuejuan Han, Xi Wang, Chen Zhou, Rui Gu, and Chen Lu. "Structure Connectivity and Substructure Connectivity of Alternating Group Graphs." In 2018 IEEE International Conference on Progress in Informatics and Computing (PIC). IEEE, 2018. http://dx.doi.org/10.1109/pic.2018.8706296.
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Bei, Xiaohui, Alexander Lam, Xinhang Lu, and Warut Suksompong. "Welfare Loss in Connected Resource Allocation." In Thirty-Third International Joint Conference on Artificial Intelligence {IJCAI-24}. California: International Joint Conferences on Artificial Intelligence Organization, 2024. http://dx.doi.org/10.24963/ijcai.2024/294.
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We study the allocation of indivisible goods that form an undirected graph and investigate the worst-case welfare loss when requiring that each agent must receive a connected subgraph. Our focus is on both egalitarian and utilitarian welfare. Specifically, we introduce the concept of egalitarian (resp., utilitarian) price of connectivity, which captures the worst-case ratio between the optimal egalitarian (resp., utilitarian) welfare among all allocations and that among the connected allocations. We provide tight or asymptotically tight bounds on the price of connectivity for various large classes of graphs when there are two agents, and for paths, stars and cycles in the general case. Many of our results are supplemented with algorithms which find connected allocations with a welfare guarantee corresponding to the price of connectivity.
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Zhuo, Wei, and Guang Tan. "Proximity Enhanced Graph Neural Networks with Channel Contrast." In Thirty-First International Joint Conference on Artificial Intelligence {IJCAI-22}. California: International Joint Conferences on Artificial Intelligence Organization, 2022. http://dx.doi.org/10.24963/ijcai.2022/340.
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We consider graph representation learning in an unsupervised manner. Graph neural networks use neighborhood aggregation as a core component that results in feature smoothing among nodes in proximity. While successful in various prediction tasks, such a paradigm falls short of capturing nodes' similarities over a long distance, which proves to be important for high-quality learning. To tackle this problem, we strengthen the graph with three types of additional graph views, in which each node is directly linked to a set of nodes with the highest similarity in terms of node features, neighborhood features or local structures. Not restricted by connectivity in the original graph, the generated views provide new and complementary perspectives from which to look at the relationship between nodes. Inspired by the recent success of contrastive learning approaches, we propose a self-supervised method that aims to learn node representations by maximizing the agreement between representations across generated views and the original graph, without the requirement of any label information. We also propose a channel-level contrast approach that greatly reduces computation cost. Extensive experiments on six assortative graphs and three disassortative graphs demonstrate the effectiveness of our approach.
Reports on the topic "Connectivité des graphes"
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Rodger, C. A., D. G. Hoffman, P. D. Johnson, and Jr. Connectivity and Colorings of Graphs. Fort Belvoir, VA: Defense Technical Information Center, March 2002. http://dx.doi.org/10.21236/ada400177.
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Feddema, John Todd, Raymond Harry Byrne, and Chaouki T. Abdallah. Algebraic connectivity and graph robustness. Office of Scientific and Technical Information (OSTI), July 2009. http://dx.doi.org/10.2172/973665.
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Zhao, Jun, Osman Yagan, and Virgil Gligor. Results on Vertex Degree and K-Connectivity in Uniform S-Intersection Graphs. Fort Belvoir, VA: Defense Technical Information Center, January 2014. http://dx.doi.org/10.21236/ada609112.
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McGlaughlin, Alec S. Analyzing and Assessing Brain Structure with Graph Connectivity Measures. Fort Belvoir, VA: Defense Technical Information Center, May 2014. http://dx.doi.org/10.21236/ada604781.
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Nieto-Castanon, Alfonso. CONN functional connectivity toolbox (RRID:SCR_009550), Version 18. Hilbert Press, 2018. http://dx.doi.org/10.56441/hilbertpress.1818.9585.
Full textAbstract:
CONN is a Matlab-based cross-platform software for the computation, display, and analysis of functional connectivity in fMRI (fcMRI). Connectivity measures include seed-to-voxel connectivity maps, ROI-to- ROI connectivity matrices, graph properties of connectivity networks, generalized psychophysiological interaction models (gPPI), intrinsic connectivity, local correlation and other voxel-to-voxel measures, independent component analyses (ICA), and dynamic component analyses (dyn-ICA). CONN is available for resting state data (rsfMRI) as well as task-related designs. It covers the entire pipeline from raw fMRI data to hypothesis testing, including spatial coregistration, ART-based scrubbing, aCompCor strategy for control of physiological and movement confounds, first-level connectivity estimation, and second-level random-effect analyses and hypothesis testing.
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Nieto-Castanon, Alfonso. CONN functional connectivity toolbox (RRID:SCR_009550), Version 20. Hilbert Press, 2020. http://dx.doi.org/10.56441/hilbertpress.2048.3738.
Full textAbstract:
CONN is a Matlab-based cross-platform software for the computation, display, and analysis of functional connectivity in fMRI (fcMRI). Connectivity measures include seed-to-voxel connectivity maps, ROI-to- ROI connectivity matrices, graph properties of connectivity networks, generalized psychophysiological interaction models (gPPI), intrinsic connectivity, local correlation and other voxel-to-voxel measures, independent component analyses (ICA), and dynamic component analyses (dyn-ICA). CONN is available for resting state data (rsfMRI) as well as task-related designs. It covers the entire pipeline from raw fMRI data to hypothesis testing, including spatial coregistration, ART-based scrubbing, aCompCor strategy for control of physiological and movement confounds, first-level connectivity estimation, and second-level random-effect analyses and hypothesis testing.
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Nieto-Castanon, Alfonso. CONN functional connectivity toolbox (RRID:SCR_009550), Version 19. Hilbert Press, 2019. http://dx.doi.org/10.56441/hilbertpress.1927.9364.
Full textAbstract:
CONN is a Matlab-based cross-platform software for the computation, display, and analysis of functional connectivity in fMRI (fcMRI). Connectivity measures include seed-to-voxel connectivity maps, ROI-to- ROI connectivity matrices, graph properties of connectivity networks, generalized psychophysiological interaction models (gPPI), intrinsic connectivity, local correlation and other voxel-to-voxel measures, independent component analyses (ICA), and dynamic component analyses (dyn-ICA). CONN is available for resting state data (rsfMRI) as well as task-related designs. It covers the entire pipeline from raw fMRI data to hypothesis testing, including spatial coregistration, ART-based scrubbing, aCompCor strategy for control of physiological and movement confounds, first-level connectivity estimation, and second-level random-effect analyses and hypothesis testing.
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Han, Guang, and Armand M. Makowski. A Strong Zero-One Law for Connectivity in One-Dimensional Geometric Random Graphs With Non-Vanishing Densities. Fort Belvoir, VA: Defense Technical Information Center, April 2007. http://dx.doi.org/10.21236/ada468079.
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Sparrow, Kent, Joseph Gutenson, Mark Wahl, and Kayla Cotterman. Evaluation of climatic and hydroclimatic resources to support the US Army Corps of Engineers Regulatory Program. Engineer Research and Development Center (U.S.), September 2022. http://dx.doi.org/10.21079/11681/45484.
Full textAbstract:
Short-term climatic and hydrologic interactions, or hydroclimatology, are an important consideration when delineating the geographic extent of aquatic resources and assessing whether an aquatic resource is a jurisdictional water of the United States (WOTUS) and is therefore subject to the Clean Water Act (CWA). The now vacated 2020 Navigable Waters Protection Rule (NWPR) required the evaluation of precipitation and other hydroclimatic conditions to assess the jurisdictional status of an aquatic resource based on normal hydroclimatic conditions. Short-term hydroclimatic conditions, such as antecedent precipitation, evapotranspiration, wetland delineation, and streamflow duration assessments, provide information on an aquatic resource’s geo-graphic extent, hydrologic characteristics, and hydrologic connectivity with other aquatic resources. Here, researchers from the US Army Corps of Engineers, Engineer Research and Development Center (ERDC) evaluate tools and data available to practitioners for assessing short-term hydroclimatic conditions. The work highlights specific meteorological phenomena that are important to consider when assessing short-term hydroclimatic conditions that affect the geographic extent and hydrologic characteristics of an aquatic resource. The findings suggest that practitioners need access to data and tools that more holistically consider the impact of short-term antecedent hydroclimatology on the entire hydrologic cycle, rather than tools based solely on precipitation.