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Characterizations of spatio-temporal complex systemsKrishan, Kapilanjan 20 May 2005 (has links)
The thesis develops two characterizations of spatio-temporal complex patterns. While these are developed for the patterns of fluid flow in experiments on Rayleigh-Benard Convection(RBC), they are adaptable to a wide range of spatially extended systems. The characterizations may be especially useful in cases where one does not have good models describing the dynamics, making numerical and analytic studies difficult.
In Spiral Defect Chaos(SDC), a weakly turbulent regime of RBC, the convective rolls exhibit complex spatial and temporal dynamics. We study the dynamics of SDC through local defect formations between convective rolls as well as the topological rearrangements of these rolls at a global scale.
A laser based thermal actuation system is developed to reproducibly impose initial states for the fluid flow and construct ensembles of trajectories in the neighborhood of defect nucleation. This is used to extract the modes and their growth rates, characterizing the linear manifold corresponding to defect nucleation. The linear manifold corresponding to instabilities resulting in defect formation is key to building efficient schemes to control the dynamics exhibited.
We also develop the use of computational homology as a tool to study spatially extended dynamical systems. A quantitative measure of the topological features of patterns is shown to provide insights into the underlying dynamics not easily uncovered otherwise. In the case of RBC, the homology of the patterns is seen to indicate asymmetries between hot and cold regions of the flow, stochastic evolution at a global scale as well as bifurcations occurring well into the turbulent regime of the flow.
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Analyse des dynamiques spatio-temporelles des systèmes de peuplement dans un contexte d'incertitude : Application à l'archéologie spatiale / Analysis of spatio-temporal dynamics of settlement systems in an uncertain context : An application to spatial archaeologyFusco, Johanna 30 March 2016 (has links)
L’incertitude inhérente à notre appréhension des systèmes de peuplement passés, engendrée par les modes de collecte ou d’enregistrement des données, mais aussi par nos modes de catégorisation et de réflexion spatio-temporelles sur cette information, conditionnent fortement les hypothèses et les résultats qui en découlent. Cette thèse, menée dans le cadre du projet PaléoSyr/PaléoLib, présente une chaîne de raisonnement méthodologique exploratoire destinée à révéler et formaliser par des méthodes d’analyse spatiale divers niveaux de connaissance et d’incertitude inhérents aux bases de données archéologiques, tout en proposant des alternatives destinées à s’écarter du conditionnement imposé par les catégories spatio-temporelles rigides telles que les périodes ou les limites de zones de prospection. Celle-ci est structurée en deux axes majeurs : le premier a pour objectif de clarifier et de synthétiser les niveaux d’information inhérents à une vaste base de données couvrant la Syrie occidentale et le Liban de -9600 av. J.-C. à nos jours, en adaptant des méthodes d’aide à la décision et d’analyse spatio-morphologique, et par des procédés de géovisualisation dans une optique exploratoire. Le second axe explore et évalue localement les impacts des divers niveaux spatio-temporels que révèlent les données par des méthodes d’analyse géostatistique et de statistique spatiale, et des niveaux d’incertitude sur notre perception du changement spatio-temporel, sur un espace situé au Nord-Ouest de la Syrie. Divers modèles des « passés possibles » du peuplement élaborés à l’aide de la logique floue seront proposés, en fonction des divers niveaux spatio-temporels et d’incertitude envisagés. / The uncertainty inherent to our comprehension of past settlement systems, generated by our ways of collecting or recording data but also by our spatio-temporal categorisation and reflexion on this information, greatly condition hypotheses and results. This thesis was carried out in the framework of PaleoSyr/PaleoLib project, and develops a methodological and exploratory reasoning chain whose aim is to reveal and formalise with spatial analysis several levels of knowledge and uncertainty which are inherent to archaeological databases. It proposes alternatives to try and avoid the conditioning imposed by rigid spatio-temporal categories such as periods or survey zones. It is organised in two major axes : the first one intends to clarify and synthetize several levels of information which are inherent to a big database covering Occidental Syria and Lebanon from -9600 B.C to the present, by adapting decision making and spatio-morphological methods, and through geovisualisation processes in an exploratory dimension. The second axis explores and evaluates locally the impacts of the various spatio-temporal and uncertainty levels revealed by data with geostatistics and spatial statistics on our perception of spatio-temporal change, on a test zone situated at the North-West of Syria. Several models of the “possible pasts” of settlement with the help of fuzzy logic are then proposed, depending on the various spatio-temporal and uncertainty levels taken into account.
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Source-Space Analyses in MEG/EEG and Applications to Explore Spatio-temporal Neural Dynamics in Human VisionYang, Ying 01 February 2017 (has links)
Human cognition involves dynamic neural activities in distributed brain areas. For studying such neural mechanisms, magnetoencephalography (MEG) and electroencephalography (EEG) are two important techniques, as they non-invasively detect neural activities with a high temporal resolution. Recordings by MEG/EEG sensors can be approximated as a linear transformation of the neural activities in the brain space (i.e., the source space). However, we only have a limited number sensors compared with the many possible locations in the brain space; therefore it is challenging to estimate the source neural activities from the sensor recordings, in that we need to solve the underdetermined inverse problem of the linear transformation. Moreover, estimating source activities is typically an intermediate step, whereas the ultimate goal is to understand what information is coded and how information flows in the brain. This requires further statistical analysis of source activities. For example, to study what information is coded in different brain regions and temporal stages, we often regress neural activities on some external covariates; to study dynamic interactions between brain regions, we often quantify the statistical dependence among the activities in those regions through “connectivity” analysis. Traditionally, these analyses are done in two steps: Step 1, solve the linear problem under some regularization or prior assumptions, (e.g., each source location being independent); Step 2, do the regression or connectivity analysis. However, biases induced in the regularization in Step 1 can not be adapted in Step 2 and thus may yield inaccurate regression or connectivity results. To tackle this issue, we present novel one-step methods of regression or connectivity analysis in the source space, where we explicitly modeled the dependence of source activities on the external covariates (in the regression analysis) or the cross-region dependence (in the connectivity analysis), jointly with the source-to-sensor linear transformation. In simulations, we observed better performance by our models than by commonly used two-step approaches, when our model assumptions are reasonably satisfied. Besides the methodological contribution, we also applied our methods in a real MEG/EEG experiment, studying the spatio-temporal neural dynamics in the visual cortex. The human visual cortex is hypothesized to have a hierarchical organization, where low-level regions extract low-level features such as local edges, and high-level regions extract semantic features such as object categories. However, details about the spatio-temporal dynamics are less understood. Here, using both the two-step and our one-step regression models in the source space, we correlated neural responses to naturalistic scene images with the low-level and high-level features extracted from a well-trained convolutional neural network. Additionally, we also studied the interaction between regions along the hierarchy using the two-step and our one-step connectivity models. The results from the two-step and the one-step methods were generally consistent; however, the one-step methods demonstrated some intriguing advantages in the regression analysis, and slightly different patterns in the connectivity analysis. In the consistent results, we not only observed an early-to-late shift from low-level to high-level features, which support feedforward information flow along the hierarchy, but also some novel evidence indicating non-feedforward information flow (e.g., topdown feedback). These results can help us better understand the neural computation in the visual cortex. Finally, we compared the empirical sensitivity between MEG and EEG in this experiment, in detecting dependence between neural responses and visual features. Our results show that the less costly EEG was able to achieve comparable sensitivity with that in MEG when the number of observations was about twice of that in MEG. These results can help researchers empirically choose between MEG and EEG when planning their experiments with limited budgets.
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Integrated Evaluation of Wastewater Irrigation for Sustainable Agriculture and Groundwater DevelopmentJampani, Mahesh 02 September 2021 (has links)
Many agricultural landscapes in India are irrigated with wastewater, and it is a common livelihood practice particularly in urban and peri-urban areas. Farmers around urban agglomerations continuously depend on the wastewater released from nearby urban centres. While providing opportunities with respect to water and nutrient supply, irrigating with wastewater has adverse environmental impacts, particularly on the local aquifer systems. Therefore, addressing the wastewater irrigation influence on local aquifer systems is crucial for sustainable groundwater management. The present research demonstrates the impacts of wastewater irrigation, seasonality and spatio-temporal variations in the groundwater quality and its geochemical evolution and mixing processes in different land use and crop settings. The doctoral research aims at understanding the aquifer heterogeneity, land use conditions, groundwater dynamics and contaminant fate and transport in the long-term wastewater irrigation system to develop sustainable and suitable groundwater management strategies. The selected study watershed is located on the banks of Musi River in a peri-urban catchment of the Musi River basin in India. Statistical techniques, land use change modelling and solute flow and transport modelling tools are employed to identify and quantify the linkages between contaminants, agricultural use and environmental variables, particularly those characterizing the groundwater qualities. The research results suggest that concentrations of the major ionic substances increase after the monsoon season, especially in wastewater irrigated areas and the major polluted groundwaters to come from the wastewater irrigated parts of the watershed. Clusters of chemical variables identified indicate that groundwater pollution is highly impacted by mineral interactions and long-term wastewater irrigation. The groundwater geochemistry of the watershed is largely controlled by long-term wastewater irrigation, local rainfall patterns and water-rock interactions. The detected land use changes in the watershed indicate that, as a consequence of urban pressures, agricultural landscapes are being converted into built-up areas and, at the same time, former barren land is converted to agricultural plots. The mapped land use data are used in modelling the aquifer conditions and to observe the groundwater dynamics in the peri-urban environment. The study results provide the basis for sustainable agriculture and groundwater development using the efficient scenarios identified for wastewater irrigation management. The resulting strategies for integrated management of water and waste will contribute to the water security and achieve the respective Sustainable Development Goals (SDGs 2, 3, 6, 11 and 15).
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Redes com dinâmica espaço-temporal e aplicações computacionais / Networks with spatio temporal dynamics in computer sciencesQuiles, Marcos Gonçalves 24 March 2009 (has links)
Nas últimas décadas, testemunhou-se um crescente interesse no estudo de sistemas complexos. Tais sistemas são compostos por pelo menos dois componentes fundamentais: elementos dinâmicos individuais e uma estrutura de organização definindo a forma de interação entre estes. Devido a dinâmica de cada elemento e a complexidade de acoplamento, uma grande variedade de fenômenos espaço-temporais podem ser observados. Esta tese tem como objetivo principal explorar o uso da dinâmica espaço-temporal em redes visando a solução de alguns problemas computacionais. Com relação aos mecanismos dinâmicos, a sincronização entre osciladores acoplados, a caminhada aleatória-determinística e a competição entre elementos na rede foram considerados. Referente à parte estrutural da rede, tanto estruturas regulares baseadas em reticulados quanto redes com estruturas mais gerais, denominadas redes complexas, foram abordadas. Este estudo é concretizado com o desenvolvimento de modelos aplicados a dois domínios específicos. O primeiro refere-se à utilização de redes de osciladores acoplados para construção de modelos de atenção visual. Dentre as principais características desses modelos estão: a seleção baseada em objetos, a utilização da sincronização/ dessincronização entre osciladores neurais como forma de organização perceptual, a competição entre objetos para aquisição da atenção. Além disso, ao comparar com outros modelos de seleção de objetos baseados em redes osciladores, um número maior de atributos visuais é utilizado para definir a saliência dos objetos. O segundo domínio está relacionado ao desenvolvimento de modelos para detecção de comunidades em redes complexas. Os dois modelos desenvolvidos, um baseado em competição de partículas e outro baseado em sincronização de osciladores, apresentam alta precisão de detecção e ao mesmo tempo uma baixa complexidade computacional. Além disso, o modelo baseado em competição de partículas não só oferece uma nova técnica de detecção de comunidades, mas também apresenta uma abordagem alternativa para realização de aprendizado competitivo. Os estudos realizados nesta tese mostram que a abordagem unificada de dinâmica e estrutura é uma ferramenta promissora para resolver diversos problemas computacionais / In the last decades, an increasing interest in complex system study has been witnessed. Such systems have at least two integrated fundamental components: individual dynamical elements and an organizational structure which defines the form of interaction among those elements. Due to the dynamics of each element and the coupling complexity, various spatial-temporal phenomena can be observed. The main objective of this thesis is to explore spatial-temporal dynamics in networks for solving some computational problems. Regarding the dynamical mechanisms, the synchronization among coupled oscillators, deterministic-random walk and competition between dynamical elements are taken into consideration. Referring to the organizational structure, both regular network based on lattice and more general network, called complex networks, are studied. The study of coupled dynamical elements is concretized by developing computational models applied to two specific domains. The first refers to the using of coupled neural oscillators for visual attention. The main features of the developed models in this thesis are: object-based visual selection, realization of visual perceptual organization by using synchronization / desynchronization among neural oscillators, competition among objects to achieve attention. Moreover, in comparison to other object-based selection models, more visual attributes are employed to define salience of objects. The second domain is related to the development of computational models applied to community detection in complex networks. Two developed models, one based on particle competition and another based on synchronization of Integrate-Fire oscillators, present high detection rate and at the same time low computational complexity. Moreover, the model based on particle competition not only offers a new community detection technique, but also presents an alternative way to realize artificial competitive learning. The study realized in this thesis shows that the unified scheme of dynamics and structure is a powerful tool to solve various computational problems
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ANTHROPISATION ET DYNAMIQUE SPATIO-TEMPORELLE DE PAYSAGES FORESTIERS EN REPUBLIQUE DEMOCRATIQUE DU CONGOBamba, Issouf 13 October 2010 (has links)
A l’image du bassin du Congo, la République Démocratique du Congo (République Démocratique du Congo) fait face à une réduction de la qualité et de la superficie de son couvert forestier. La présente étude avait pour objectif d’étudier l’effet de l’anthropisation, à travers la présence et les activités humaines sur la dynamique des paysages forestiers en République Démocratique du Congo. L’écologie du paysage, en tant que science pluridisciplinaire offre une très bonne approche à travers les indices et une méthodologie alliant la structure et la composition du paysage pour mettre en évidence les causes et les conséquences des processus écologiques. Ces approches sont basées sur le fait que en analysant la structure du paysage, des déductions utiles au sujet des processus écologiques fondamentaux peuvent être faites et vice versa. Les résultats ont montré, en quantifiant la dynamique spatio-temporelle de l’occupation du sol et par l’analyse et la caractérisation de la structure spatiale, que l’anthropisation est le moteur de la dynamique dans ces milieux forestiers. L’impact humain se traduit par une déstabilisation ou un dysfonctionnement des écosystèmes forestiers entraînant la dégradation, la fragmentation et la déforestation. Ainsi il a été montré que la proximité des villes est fortement corrélée à la dégradation et la perte d’habitats forestiers. Cela est fonction de l’importance socio-économique de ces villes car plus la ville est importante, plus elle attire la population ; que la densité de la population influence la fragmentation et l’incursion dans la forêt se fait en suivant les pistes et les routes mises en place généralement par les sociétés d’exploitation forestière. Le tout amplifié par la situation socio-économique difficile des populations et le manque de politiques de gestion appropriées de la part des gestionnaires publiques. Cette dynamique régressive du paysage forestier en République Démocratique du Congo aura une incidence négative sur les cycles climatiques globaux vu que le bassin du Congo est le plus grand bloc forestier après le bloc de l’Amazonie. La présente étude est donc un argument supplémentaire qui milite en faveur de la nécessité de prendre en compte les caractéristiques des populations locales dans les programmes de gestion de la forêt du bassin du Congo pour un meilleur équilibre écologique de la planète. / Like Congo basin, Democratic Republic of Congo’s forest covers are facing their reduction in quality and size. This study aimed to investigate the effect of human impact on forest landscape dynamics in DR Congo, through the human presence and its activities. Landscape ecology as a multidisciplinary science offers a very good approach through the index and a methodology combining the structure and the composition of the landscape to highlight the causes and the consequences of ecological processes. These approaches are based on the fact that by analyzing the structure of landscape, useful deductions about the underlying ecological processes can be made and vice versa. By quantifying the spatio-temporal dynamics of land use and by analysis and characterization of spatial structure, our results showed that anthropization is the driver of the dynamics in these forest environments. Human impact results in a destabilization or a dysfunction of the forest ecosystems involving degradation, fragmentation and deforestation. Thus it was shown that proximity to cities is strongly correlated to the degradation and loss of forest habitats. This depends on the socioeconomic importance of these cities because more the city is important, more it attracts people. Population density influences the fragmentation and the incursion into the forest is done by following the tracks and roads generally implemented by the logging companies. All amplified by socio-economic problems of population and lack of appropriate management policies on the part of public managers.This regressive dynamic forest landscape in République Démocratique du Congo will have a negative impact on global climate cycles because the Congo Basin is the largest forest block after Amazonia block. This study is another argument which advocates the need to take into account the characteristics of local population in forest management programs in the Congo Basin for a better ecological balance of planet.
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Espaces, liens, et santé : dynamiques d’invasion d’un hôte de zoonoses dans un territoire en mutation : le cas du rat noir au Sénégal Oriental / Space, Spatial relationships, and Health : spatial diffusion of an invasive host of zoonosis in a changing territory. : The black rat in southeastern SenegalLucaccioni, Héloïse 13 December 2016 (has links)
L’évolution des mises en liens en réponse aux changements globaux et à la globalisation contemporaine précipite le risque d’émergence infectieuse. Dans cette recherche, nous dressons une géographie des vulnérabilités territoriales face à l’émergence des risques zoonotiques. Notre cas d’étude est celui des dynamiques d’invasion d’un hôte commensal, le rat noir (Rattus rattus), dans les marges orientales du Sénégal, périphérie rurale ouest-africaine en mutation. Nous défendons l’idée que les sociétés façonnent des systèmes territoriaux inégalement vulnérables à la diffusion spatiale de l’hôte.Nous montrons que les espaces du Sénégal Oriental et leurs mises en liens se transforment sous l’action des multiples acteurs territoriaux. Les dynamiques d’invasion du rat noir reflètent ces évolutions. Pourtant, les facteurs spatiaux de diffusion des lieux, des foyers, et des chemins d’invasion sont inopérants pour expliquer les dynamiques spatio-temporelles de l’hôte. En outre, la distribution spatiale du rongeur apparaît en contradiction avec les modèles classiques de diffusion fondés sur la hiérarchie ou la distance spatiale des lieux. La diffusion de l’hôte s’inscrit dans des systèmes complexes et multiscalaires tissés dans la rencontre des espaces, des lieux, et des liens construits par les sociétés. Nous proposons une grille de lecture où les formes de la diffusion dans l’espace et le temps répondent des degrés de stabilité et d’instabilité de ces systèmes socio-spatiaux, façonnant ainsi des territoires inégalement vulnérables au risque d’émergence infectieuse. / The evolution of spatial relationships in the contemporary context of global changes and globalization promote disease emergence. In this study, we draw a geography of territorial vulnerabilities to the emergence of zoonotic risks. In southeastern Senegal, a changing rural periphery of West Africa, we address the issue of the spread of an invasive species and host of pathogens, the black rat (Rattus rattus). We argue that societies produce territorial systems that are unequally vulnerable to the spatial diffusion of the host.We evidence that the spaces of Southeastern Senegal and the spatial relationships among them are transformed under the action of multiple social actors. The spread of the black rat reflects these changes. Yet, the spatial characteristics of the invaded places (such as connectivity or centrality) as well as the spatial relationships among them are insufficient in understanding the spatial and temporal dynamics of the rodent invasion. Moreover, the spatial distribution of the black rat contradicts conventional models of hierarchical or contagious diffusion. The spatial diffusion of the host responds to spaces, places, and spatial links intimately woven by societies into complex and multiscale systems. We propose to understand the many forms of spatial diffusion as the response to the stability or instability of these socio-spatial systems, which then form territories unevenly vulnerable to the risk of disease emergence.
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Redes com dinâmica espaço-temporal e aplicações computacionais / Networks with spatio temporal dynamics in computer sciencesMarcos Gonçalves Quiles 24 March 2009 (has links)
Nas últimas décadas, testemunhou-se um crescente interesse no estudo de sistemas complexos. Tais sistemas são compostos por pelo menos dois componentes fundamentais: elementos dinâmicos individuais e uma estrutura de organização definindo a forma de interação entre estes. Devido a dinâmica de cada elemento e a complexidade de acoplamento, uma grande variedade de fenômenos espaço-temporais podem ser observados. Esta tese tem como objetivo principal explorar o uso da dinâmica espaço-temporal em redes visando a solução de alguns problemas computacionais. Com relação aos mecanismos dinâmicos, a sincronização entre osciladores acoplados, a caminhada aleatória-determinística e a competição entre elementos na rede foram considerados. Referente à parte estrutural da rede, tanto estruturas regulares baseadas em reticulados quanto redes com estruturas mais gerais, denominadas redes complexas, foram abordadas. Este estudo é concretizado com o desenvolvimento de modelos aplicados a dois domínios específicos. O primeiro refere-se à utilização de redes de osciladores acoplados para construção de modelos de atenção visual. Dentre as principais características desses modelos estão: a seleção baseada em objetos, a utilização da sincronização/ dessincronização entre osciladores neurais como forma de organização perceptual, a competição entre objetos para aquisição da atenção. Além disso, ao comparar com outros modelos de seleção de objetos baseados em redes osciladores, um número maior de atributos visuais é utilizado para definir a saliência dos objetos. O segundo domínio está relacionado ao desenvolvimento de modelos para detecção de comunidades em redes complexas. Os dois modelos desenvolvidos, um baseado em competição de partículas e outro baseado em sincronização de osciladores, apresentam alta precisão de detecção e ao mesmo tempo uma baixa complexidade computacional. Além disso, o modelo baseado em competição de partículas não só oferece uma nova técnica de detecção de comunidades, mas também apresenta uma abordagem alternativa para realização de aprendizado competitivo. Os estudos realizados nesta tese mostram que a abordagem unificada de dinâmica e estrutura é uma ferramenta promissora para resolver diversos problemas computacionais / In the last decades, an increasing interest in complex system study has been witnessed. Such systems have at least two integrated fundamental components: individual dynamical elements and an organizational structure which defines the form of interaction among those elements. Due to the dynamics of each element and the coupling complexity, various spatial-temporal phenomena can be observed. The main objective of this thesis is to explore spatial-temporal dynamics in networks for solving some computational problems. Regarding the dynamical mechanisms, the synchronization among coupled oscillators, deterministic-random walk and competition between dynamical elements are taken into consideration. Referring to the organizational structure, both regular network based on lattice and more general network, called complex networks, are studied. The study of coupled dynamical elements is concretized by developing computational models applied to two specific domains. The first refers to the using of coupled neural oscillators for visual attention. The main features of the developed models in this thesis are: object-based visual selection, realization of visual perceptual organization by using synchronization / desynchronization among neural oscillators, competition among objects to achieve attention. Moreover, in comparison to other object-based selection models, more visual attributes are employed to define salience of objects. The second domain is related to the development of computational models applied to community detection in complex networks. Two developed models, one based on particle competition and another based on synchronization of Integrate-Fire oscillators, present high detection rate and at the same time low computational complexity. Moreover, the model based on particle competition not only offers a new community detection technique, but also presents an alternative way to realize artificial competitive learning. The study realized in this thesis shows that the unified scheme of dynamics and structure is a powerful tool to solve various computational problems
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Nächste-Nachbar basierte Methoden in der nichtlinearen Zeitreihenanalyse / Nearest-neighbor based methods for nonlinear time-series analysisMerkwirth, Christian 02 November 2000 (has links)
No description available.
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Dynamique spatio-temporelle de circuits de réentrée chez le sujet humain et dans un modèle d'infarctus du myocarde chez le chienHélie, François January 2002 (has links)
Thèse numérisée par la Division de la gestion de documents et des archives de l'Université de Montréal
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