Tesis sobre el tema "Série temporelle en flux"
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Peng, Tao. "Analyse de données loT en flux". Electronic Thesis or Diss., Aix-Marseille, 2021. http://www.theses.fr/2021AIXM0649.
Texto completoSince the advent of the IoT (Internet of Things), we have witnessed an unprecedented growth in the amount of data generated by sensors. To exploit this data, we first need to model it, and then we need to develop analytical algorithms to process it. For the imputation of missing data from a sensor f, we propose ISTM (Incremental Space-Time Model), an incremental multiple linear regression model adapted to non-stationary data streams. ISTM updates its model by selecting: 1) data from sensors located in the neighborhood of f, and 2) the near-past most recent data gathered from f. To evaluate data trustworthiness, we propose DTOM (Data Trustworthiness Online Model), a prediction model that relies on online regression ensemble methods such as AddExp (Additive Expert) and BNNRW (Bagging NNRW) for assigning a trust score in real time. DTOM consists: 1) an initialization phase, 2) an estimation phase, and 3) a heuristic update phase. Finally, we are interested predicting multiple outputs STS in presence of imbalanced data, i.e. when there are more instances in one value interval than in another. We propose MORSTS, an online regression ensemble method, with specific features: 1) the sub-models are multiple output, 2) adoption of a cost sensitive strategy i.e. the incorrectly predicted instance has a higher weight, and 3) management of over-fitting by means of k-fold cross-validation. Experimentation with with real data has been conducted and the results were compared with reknown techniques
Rossi, Aurélien. "Analyse spatio-temporelle de la variabilité hydrologique du bassin versant du Mississippi : rôles des fluctuations climatiques et déduction de l'impact des modifications du milieu physique". Rouen, 2010. http://www.theses.fr/2010ROUES013.
Texto completoGreat River watersheds, as the Mississippi River in North America, integrate climate and environmental changes (climate fluctuations, precipitations, streamflow, sediment loads) at near-continent scale, as well as anthropogenic changes in physical environment (land uses, river management. . . ) in their hydrologic response, which makes sometimes difficult the identification of linkages between hydrological and climate variability. The main objectives of this work is to determine and quantify the relationships between hydrological variability and climate fluctuations (regionalized precipitations, climate indices) of the Mississippi River and its main tributaries, using spectral approaches adapted to (the study of non-stationary processes (continuous wavelet transform, wavelet coherence). Hydrological variability of the Mississippi River and its main tributaries is structured by several scales of variability, from annual to inter-annual (2-4y, 3-6y, 5-8y), decadal (8-16y, 12-16y) and multi-decadal scales (22y, 22-26y). These modes of streamflow variability are very similar to those observed in regionalized precipitations (mean coherency is estimated from 77% to 89% according to the sub-watershed), and operates at same time-scales variability of the main climate fluctuations affecting this region (ENSO, PDO, AMO, NAO, NAM et PNA), preliminary identified and synthesized using an similar methodology. Streamflow variability of the Mississippi River watershed appears influenced by several teleconnections (mean coherency of 63% to 66% with all climate indices), which operate at different spatial and temporal scales and change across time. Furthermore and not surprisingly, the hydrological variability of the Mississippi River and its main tributaries appears to be closely linked to a major shift in the climate system – as well as many other hydrosystems around the world – observed at global scale around 1970. This change would result in an increase in both streamflow mean and variance, as highlighted by changes in the spectral content of climate and hydrological parameters. In this way, a so-called "hydro-climatic" index was proposed in order to resume all those characteristics of the climate system that would imprint the typical scales of variability detected in the hydrological processes analyzed according to each sub-watershed. Finally, even if the majority of hydrological parameters appears strongly affected by climate parameters, others factors such as changes in physical environment (land use, river management. . . ) could also significantly influence hydrological parameters (e. G. Low and high streamflow). We could detect such human-induced changes in the variability of suspended sediment loads and show that it involved a decrease in suspended sediment loads up to 2,25. 108 metric t. Y-1 between 1950 and 1975 using a spectral modelling approach. However, the influence of these physical environmental changes in hydrology would be associated to trends or to very localized changes in space and time, rather than associated to the existence of oscillations in hydrological parameters as we could detect them. We then conclude that, despite the potential strong influence of environmental changes, climate fluctuations remain the main factor involved in the observed hydrological changes
Viinikka, Jouni. "Traitement de flux d'alertes en détection d'intrusions avec des méthodes d'analyse de séries temporelles". Caen, 2006. http://www.theses.fr/2006CAEN2054.
Texto completoThe first intrusion detection systems were used to detect the breaches of the security policy. This remains their main use today, but complementary and alternative usages are more and more common. For example, some network-based sensors can be used to monitor network management and control traffic, i. E. , normal system functioning. Typically, intrusion detection systems generate large numbers of alerts. This is especially the case with these complementary usages: this thesis focuses on analyzing and processing this type of alerts. Real world alert flows are analyzed to demonstrate that a significant proportion of the alerts can be caused by normal system use. For this reason, some alert flows contain strong regular behaviors. This being established, we propose three different alert flow processing methods. The methods build on techniques from time series analysis, namely exponentially weighted moving averages, and both stationary and non-stationary autoregressive modeling. With these techniques, we first model the normal behavior of alert flows, and then filter out alerts related to the normal use of the monitored system. Our goal is to reduce the workload of the security operator, and to provide him information that is not available by analyzing alerts individually. Experimental results show that this goal is reached
Rhéaume, François. "Une méthode de machine à état liquide pour la classification de séries temporelles". Thesis, Université Laval, 2012. http://www.theses.ulaval.ca/2012/28815/28815.pdf.
Texto completoThere are a number of reasons that motivate the interest in computational neuroscience for engineering applications of artificial intelligence. Among them is the speed at which the domain is growing and evolving, promising further capabilities for artificial intelligent systems. In this thesis, a method that exploits the recent advances in computational neuroscience is presented: the liquid state machine. A liquid state machine is a biologically inspired computational model that aims at learning on input stimuli. The model constitutes a promising temporal pattern recognition tool and has shown to perform very well in many applications. In particular, temporal pattern recognition is a problem of interest in military surveillance applications such as automatic target recognition. Until now, most of the liquid state machine implementations for spatiotemporal pattern recognition have remained fairly similar to the original model. From an engineering perspective, a challenge is to adapt liquid state machines to increase their ability for solving practical temporal pattern recognition problems. Solutions are proposed. The first one concentrates on the sampling of the liquid state. In this subject, a method that exploits frequency features of neurons is defined. The combination of different liquid state vectors is also discussed. Secondly, a method for training the liquid is developed. The method implements synaptic spike-timing dependent plasticity to shape the liquid. A new class-conditional approach is proposed, where different networks of neurons are trained exclusively on particular classes of input data. For the suggested liquid sampling methods and the liquid training method, comparative tests were conducted with both simulated and real data sets from different application areas. The tests reveal that the methods outperform the conventional liquid state machine approach. The methods are even more promising in that the results are obtained without optimization of many internal parameters for the different data sets. Finally, measures of the liquid state are investigated for predicting the performance of the liquid state machine.
Pealat, Clément. "Modélisation du flux de patients aux urgences liés aux maladies respiratoires par analyse géométrique de séries temporelles". Thesis, Lyon, 2022. http://www.theses.fr/2022LYSEI017.
Texto completoEvery year, during the winter period, hospitals are deeply impacted by the arrival of winter viruses. These winter viruses, influenza and RSV, are difficult to anticipate. Indeed, these epidemic phenomena are not perfectly periodic and have an impact mainly on the length of stay of patients rather than on the number of arrivals. It is therefore not possible to anticipate these epidemics by directly analyzing the number of patients arriving in the emergency department per day. A posteriori, in order to have an image of the epidemic, PCR tests are carried out on the hospital's patients. In addition, a patient arriving at the emergency department is immediately classified according to his symptoms. We then propose to gather the positive PCR tests and the number of arrivals per symptom via time series clustering. This highlights the symptoms related to viruses. Thus, to anticipate an arrival of an epidemic in a near future, we can use the number of arrivals for the virus marker symptoms rather than the total number of arrivals at the emergency department. To achieve this clustering, we propose an innovative method based on a geometric representation of time series. In particular, we highlight the efficiency of using the Riemmannian geometry applied to the Grassmann manifold (via a representation on the Stiefel manifold) to analyze time series
Zuo, Jingwei. "Apprentissage de représentations et prédiction pour des séries-temporelles inter-dépendantes". Electronic Thesis or Diss., université Paris-Saclay, 2022. http://www.theses.fr/2022UPASG038.
Texto completoTime series is a common data type that has been applied to enormous real-life applications, such as financial analysis, medical diagnosis, environmental monitoring, astronomical discovery, etc. Due to its complex structure, time series raises several challenges in their data processing and mining. The representation of time series plays a key role in data mining tasks and machine learning algorithms for time series. Yet, a few methods consider the interrelation that may exist between different time series when building the representation. Moreover, the time series mining requires considering not only the time series' characteristics in terms of data complexity but also the concrete application scenarios where the data mining task is performed to build task-specific representations.In this thesis, we will study different time series representation approaches that can be used in various time series mining tasks, while capturing the relationships among them. We focus specifically on modeling the interrelations between different time series when building the representations, which can be the temporal relationship within each data source or the inter-variable relationship between various data sources. Accordingly, we study the time series collected from various application contexts under different forms. First, considering the temporal relationship between the observations, we learn the time series in a dynamic streaming context, i.e., time series stream, for which the time series data is continuously generated from the data source. Second, for the inter-variable relationship, we study the multivariate time series (MTS) with data collected from multiple data sources. Finally, we study the MTS in the Smart City context, when each data source is given a spatial position. The MTS then becomes a geo-located time series (GTS), for which the inter-variable relationship requires more modeling efforts with the external spatial information. Therefore, for each type of time series data collected from distinct contexts, the interrelations between the time series observations are emphasized differently, on the temporal or (and) variable axis.Apart from the data complexity from the interrelations, we study various machine learning tasks on time series in order to validate the learned representations. The high-level learning tasks studied in this thesis consist of time series classification, semi-supervised time series learning, and time series forecasting. We show how the learned representations connect with different time series learning tasks under distinct application contexts. More importantly, we conduct the interdisciplinary study on time series by leveraging real-life challenges in machine learning tasks, which allows for improving the learning model's performance and applying more complex time series scenarios.Concretely, for these time series learning tasks, our main research contributions are the following: (i) we propose a dynamic time series representation learning model in the streaming context, which considers both the characteristics of time series and the challenges in data streams. We claim and demonstrate that the Shapelet, a shape-based time series feature, is the best representation in such a dynamic context; (ii) we propose a semi-supervised model for representation learning in multivariate time series (MTS). The inter-variable relationship over multiple data sources is modeled in a real-life context, where the data annotations are limited; (iii) we design a geo-located time series (GTS) representation learning model for Smart City applications. We study specifically the traffic forecasting task, with a focus on the missing-value treatment within the forecasting algorithm
Assaad, Aziz. "Pollution anthropique de cours d'eau : caractérisation spatio-temporelle et estimation des flux". Thesis, Université de Lorraine, 2014. http://www.theses.fr/2014LORR0054/document.
Texto completoThe Water Framework Directive demands a return to good condition for rivers in Europe. These rivers receive different types of pollution related to various economic activities of populations installed along their banks. We are often interested in an isolated manner to particular types of pollution: pollution due to agricultural pesticides, fertilizers and livestock waste in rural areas, pollution due to a specific industry (steel, paper mill, etc.), more or less well treated domestic pollution, etc. But in many cases, we are dealing with a mixture of pollutants. In the case of the Moselle, the pollution generated by human activities in the French part of the Moselle watershed impacts surface water quality downstream and therefore the Rhine. Our goal is to characterize the state of some tributaries of the Moselle (Madon, Meurthe, Vologne and Fensch) versus anthropogenic pressures and propose a strategy to calculate the flow of pollutants along these rivers. In this context, sampling campaigns with a dense spatial stations have been organized. In addition to the usual parameters characterizing water quality (conductivity, pH, dissolved organic carbon, ammonia nitrogen, nitrate, etc.) a particular attention has been given to optical properties (UV-visible absorbance, synchronous fluorescence) of dissolved organic matter in order to understand its origin. Synchronous fluorescence spectra were studied by deconvolution or by principal components analysis. A method has been developed, based on the synchronous fluorescence spectroscopy, to detect the presence of optical brighteners. Finally, a methodology has been developed in Madon watershed in order to calculate the mean daily pollution flux at each sampling station for each sampling period from geographic data
Dubreuil, Céline. "Variabilité spatio-temporelle de l'ultraplancton dans le secteur indien de l'océan Austral". Aix-Marseille 2, 2003. http://www.theses.fr/2003AIX22097.
Texto completoFoulon, Lucas. "Détection d'anomalies dans les flux de données par structure d'indexation et approximation : Application à l'analyse en continu des flux de messages du système d'information de la SNCF". Thesis, Lyon, 2020. http://www.theses.fr/2020LYSEI082.
Texto completoIn this thesis, we propose methods to approximate an anomaly score in order to detect abnormal parts in data streams. Two main problems are considered in this context. Firstly, the handling of the high dimensionality of the objects describing the time series extracted from the raw streams, and secondly, the low computation cost required to perform the analysis on-the-fly. To tackle the curse of dimensionality, we have selected the CFOF anomaly score, that has been proposed recently and proven to be robust to the increase of the dimensionality. Our main contribution is then the proposition of two methods to quickly approximate the CFOF score of new objects in a stream. The first one is based on safe pruning and approximation during the exploration of object neighbourhood. The second one is an approximation obtained by the aggregation of scores computed in several subspaces. Both contributions complete each other and can be combined. We show on a reference benchmark that our proposals result in important reduction of the execution times, while providing approximations that preserve the quality of anomaly detection. Then, we present our application of these approaches within the SNCF information system. In this context, we have extended the existing monitoring modules by a new tool to help to detect abnormal behaviours in the real stream of messages within the SNCF communication system
Nasseh, Azeddine. "Flux et variabilité spatio-temporelle des transports dissous et particulaires dans le bassin de l'Orne". Doctoral thesis, Universite Libre de Bruxelles, 1997. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/212146.
Texto completoPéretié, Guilhem. "Segmentation spatio-temporelle temps-réel de flux vidéo pour un encodage dépendant de son contenu". Bordeaux 1, 2007. http://www.theses.fr/2007BOR13355.
Texto completoThe work presented in this document was accomplished within the framework of a purse CIFRE, i. E. A partnership between the university, a PhD Student and a company. They correspond to two projects being integrated in a common environment: The extraction of the content natural or encoded videos for their characterization. Developed in an enterprise environment, they are meant to offer concrete and innovating solutions vis-a-vis the technological and economical challenges with which the enterprise is confronted. They are presented in two parts. The first one will be dealing with the pixel-based characterization of the images according to the visual attention of an observer, for a selective reduction of information in preparation to the encoding phase. The second part will describe a method of adaptation of a video flow (transrating) in real time, by putting a modification of the flow «done on the flight » of pre-encoded videos
NASSEH, AZEDDINE. "Flux et variabilite spatio-temporelle des transports dissous et particulaires dans le bassin de l'orne". Caen, 1997. http://www.theses.fr/1997CAEN2078.
Texto completoBoileau, Donald. "Modélisation spatio-temporelle pour la détection d’événements de sécurité publique à partir d’un flux Twitter". Mémoire, Université de Sherbrooke, 2017. http://hdl.handle.net/11143/10241.
Texto completoAbstract : Twitter is a social media that is very popular in North America, giving law enforcement agencies an opportunity to detect events of public interest. Twitter messages (tweets) tied to an event often contain street names, indicating where this event takes place, which can be used to infer the event's geographical coordinates in real time. Many commercial software tools are available to monitor social media. The performance of these tools could be greatly improved with a larger sample of tweets, a sorting mechanism to identify pertinent events more quickly and to measure the reliability of the detected events. The goal of this master‟s thesis is to detect, from a public Twitter stream, events relative to public safety of a territory, automatically and with an acceptable level of reliability. To achieve this objective, a computer model based on four components has been developed: a) capture of public tweets based on keywords with the application of a geographic filter, b) natural language processing of the text of these tweets, use of a street gazetteer to identify tweets that can be localized and geocoding of tweets based on street names and intersections, c) a spatio-temporal method to form tweet clusters and, d) event detection by isolating clusters containing at least two tweets treating the same subject. This research project differs from existing scientific research as it combines natural language processing, search and geocoding of toponyms based on a street gazetteer, the creation of clusters using geomatics and identification of event clusters based on common tweets to detect public safety events in a Twitter public stream. The application of the model to the 90,347 tweets collected for the Toronto-Niagara region in Ontario, Canada has resulted in the identification and geocoding of 1,614 tweets and the creation of 172 clusters from which 79 event clusters contain at least two tweets having the same subject showing a reliability rate of 45.9 %.
Rangama, Yvan. "variabilite spatio-temporelle des flux air-mer de CO2 dans l'ocean sud : apport des mesures satellitaires". Phd thesis, Université Pierre et Marie Curie - Paris VI, 2004. http://tel.archives-ouvertes.fr/tel-00007529.
Texto completoRangama, Yvan. "Variabilité spatio-temporelle des flux air-mer de CO2 dans l'océan sud : apport des mesures satellitaires". Paris 6, 2004. http://www.theses.fr/2004PA066573.
Texto completoSeuront, Laurent. "Hétérogénéité spatio-temporelle et couplage physique-biologie en écologie pélagique : implications sur les flux de carbone". Lille 1, 1999. https://pepite-depot.univ-lille.fr/LIBRE/Th_Num/1999/50376-1999-401-1.pdf.
Texto completoHugueney, Bernard. "Représentations symboliques de longues séries temporelles". Paris 6, 2003. http://www.theses.fr/2003PA066161.
Texto completoTran, Dinh Trong. "Analyse rapide et robuste des solutions GPS pour la tectonique". Phd thesis, Université Nice Sophia Antipolis, 2013. http://tel.archives-ouvertes.fr/tel-00868030.
Texto completoArmijos, Cardenas Elisa Natalia. "Propagation des flux de sédiments en suspension sur l'Amazone de Tamshiyacu (Pérou) à Obidos (Brésil) : variabilité spatio-temporelle". Thesis, Toulouse 3, 2015. http://www.theses.fr/2015TOU30332/document.
Texto completoThe sediments flux in Amazon Basin have an important role on the aquatic biodiversity and richness in the floodplains because the nutrients and organic matter attached on suspended sediments are deposited in these zones. The aim of this study is to understand the spatial and temporal distribution of sediments flux in the Amazon River, therefore were select four gauging station located along of Amazon Riven from Peru to Brazil. In each gauging station was make superficial samples each ten days and samples in the section in different times of hydrological period. Turbidity profiles and granulometry measuring were made too in each gauging station. In the Andean region, it is observed a relationship between the suspended sediments concentration and discharge, however, this relationship become a hysteresis in the plain especially in the Óbidos gauging station located at 870 km before of mouth. This result can be by the contribution of influx poor in suspended sediments from Guyanese and Brazilian shields. In 3000 km of long from Peru to Brazil plain, the suspended sediments is composed by two well-defined types of suspended sediments: fine sediments (10-20 µm) and coarse sediments (100-250 µm). The percentage of each type of sediments in the main river is different during the hydrologic regime. Peak of fine sediments is observed in the same period of peak of rainfall (December to March) and peak of coarse sediments is observed in flood period (May to July). The Andean and sub-Andean basin gauging station show the coarse sediments in surface due to great turbulence and low depths. Therefore, this gauging station show a relationship between the suspended sediments concentration in surface and average suspended sediments concentration in section, with this relation is possible to calculate the suspended sediments flux. Hence the Peruvian basin provide 540 Mt year -1. However in the Brazilian plain the context is different, the depth is from 40 to 100 m, becoming almost null the presence of coarse sediments in the surface. Therefore, cannot use the relationship between suspended sediments concentration in surface and average suspended sediments concentration in section. When the Óbidos gauging station is analysed, it found there is a relationship between suspended sediments concentration in surface and average of fine suspended sediments concentration. It is observed too, that there is the relationship between coarse suspended sediments concentration and discharge. Therefore, it is possible to calculate of suspended sediments flux using these two relationships. The Amazon River export 1100 Mt year-1 of suspended sediments at Óbidos gauging station, of which 60% correspond at fine sediments flux and 40% to coarse sediments flux. It is observed that the suspended sediments are sensitivity of climate variability, generally El Niño events is associate with increase of fine suspended sediments and La Niña events increase a percentage of coarse sediments in Amazon River. It is using the turbidity for determinate of suspended sediments concentration, we use this technique due the high frequency in acquisition of data. However for use the turbidity is necessary the previous calibration. It was observed that the turbidity signal is an addition to the signal emitted by the particles in one sample and with this assumption the Rose model was used to separate the concentration signal obtained by the turbidity of the two types of sediments present in the Amazon River, fine particles and sand. Therefore, it was obtained the concentration profiles to fine sediments and the concentration profiles to the sand. It is observed during the rising period that the fine sediments profiles show a strong gradient, however in the flood periods this gradient reduce come a constant in all section. These results show that turbidity and Rouse model can be used for prediction of suspended concentration in Amazon River
Dkhil, Abdellatif. "Identification systématique de structures visuelles de flux physique de production". Strasbourg, 2011. http://www.theses.fr/2011STRA6012.
Texto completoThis research is motivated by the competitive environment of manufacturing companies. It mainly concerns the design of physical production systems. Specifically, the framework study is performed during the preliminary design phase. This phase is particularly sensitive and plays a major role, where different point of views can be considered to realize the conceptual design. Only one view point concerning the static production flow is considered in this work. To generate a conceptual design depending on this point of view, a usual method of conceptual design elaboration is used. This method is introduced in many literatures. It looks like a string of data processing generated by three main activities. The first activity allows the extraction of data flow from product routing data. During the second activity, properties of analysis are used to analyze the data flow. The single or combined analysis results are called visual structures. The third activity allows the drawings of production flow graph using visual structures. After a literature review, 44 properties analysis are obtained. From these properties of analysis we can deduce 1. 75 1013 possible visual structures and the same number of production flow graphs. Recognizing this, a scientific problem of model reduction based on expert knowledge is defined. Here, the model reduction is a restriction process based on expert rules and validated with industrial data. Through this restriction process, three contributions are proposed. The first concerns the identification of referential properties of analysis which are considered the most useful and relevant in preliminary design phase. The second allows the identification of referential visual structures. The third contribution is a method to automatically identify the particular visual structures. In order to evaluate these contributions, an industrial case study is proposed
Jacquin, Anne. "Dynamique de la végétation des savanes en lien avec l’usage des feux à Madagascar : analyse par série temporelle d’images de télédétection". Phd thesis, Toulouse, INPT, 2010. http://oatao.univ-toulouse.fr/7223/1/jacquin.pdf.
Texto completoDemaio, Beatrice <1996>. "J’écoute, je traduis, j’apprends. Proposition de traduction en italien et de didactisation de la série audio « L’Épopée Temporelle » de Cyprien Iov". Master's Degree Thesis, Università Ca' Foscari Venezia, 2022. http://hdl.handle.net/10579/20972.
Texto completoPiel, Ariane. "Reconnaissance de comportements complexes par traitement en ligne de flux d’événements". Thesis, Paris 13, 2014. http://www.theses.fr/2014PA132026/document.
Texto completoRecognising complex predefined behaviours by the analysis of event flows (Complex Event Processing - CEP) alows to interpret and react to large quantities of data wich one would not be able to apprehend alone. In this Ph.D. thesis, we provide a general theoretical framework for CEP through a purely formal approach ensuring the possibility to check and analyse the recognition process. We define a language, the chronicle language, allowing the description of the complex behaviours to be recognised. We formalise the notion of chronicle recognition through a set semantics based on an arborescent representation of recognitions. In order to use this framework, we then develop two models of the recognition process. The first relies on coloured Petri nets and allows the validation of recognition principles including concurrency and modularity issues. The second model directly implements the mathematical formalism in a C++ library, chronicle recognition library (CRL), wich is avaible in open source. We use this implementation to fulfil two applications linked to the insertion of unmanned aircraft system inside air traffic in case of communication link breakdowns. This application allows, on the other hand, to check the consistency of the procedures currently followed in case of failures ; and, on the other hand, to complete these procedures with alarms in case of unavoidable situations caused by human errors. The second application oversees that the security procedures of an unmanned aircraft flying through controlled or uncontrolled airspace are correctly followed
Thyssen, Melilotus. "Analyse à haute fréquence spatiale et temporelle du phytoplancton à l'aide de la cytométrie en flux automatisée et immergeable". Aix-Marseille 2, 2008. http://theses.univ-amu.fr.lama.univ-amu.fr/2008AIX22008.pdf.
Texto completoREMOUDAKI, EMMANOUELA. "Etude des processus controlant la variabilite temporelle des flux atmospheriques de polluants et de poussieres minerales en mediterranee occidentale". Paris 7, 1990. http://www.theses.fr/1990PA077219.
Texto completoMANCIER, CHRISTELLE. "Variabilite spatiale et temporelle de l'occurrence des foliations de tropopause : estimation du flux regional d'ozone a travers la tropopause". Paris 7, 1998. http://www.theses.fr/1998PA077098.
Texto completoEspinoza, Villar Raúl. "Suivi de la dynamique spatiale et temporelle des flux sédimentaires dans le bassin de l'Amazone à partir d'images satellite". Toulouse 3, 2013. http://thesesups.ups-tlse.fr/2550/.
Texto completoThe objective of this thesis is to characterize the sedimentary fluxes of the main Amazonian rivers, using the remote sensing monitoring of their water optical properties. The field campaigns provided main characteristics of hydrological fluxes, suspended sediment (SS) and their apparent optical properties. Remote sensing reflectance is well correlated with the SS concentration in the infrared (r² = 0. 81-840 0. 9), without saturation between 500 - 850 nm. MODIS data was chosen in this study because of their high acquisition frequency. However, the use of such images is complicated because of the small size of the river steam in comparison to the pixel size. An algorithm was developed in order to automatically identify the pure water pixels into the MODIS images. The fluvial water reflectance calculated with the algorithm is validated with the in-situ radiometric data previously described, with a good precision. This algorithm is used to process automatically MODIS temporal series, along the Amazon River in Peru and the Madeira River in Brazil to check the quality of satellite estimates and understand the temporal and spatial variability of hydrosedimentary processes. This thesis demonstrates, for the first time, that the suspended sediment optical properties in a large watershed are spatially and temporally stable enough to allow effective monitoring of surface sediment flow using remote sensing
Houfaidi, Souad. "Robustesse et comportement asymptotique d'estimateurs des paramètres d'une série chronologique : (AR(P) et ARMA(P, Q))". Nancy 1, 1986. http://www.theses.fr/1986NAN10065.
Texto completoHimdi, Khalid El. "Séries chronologiques binaires avec récompenses : Applications à la modélisation en climatologie". Grenoble 1, 1986. http://tel.archives-ouvertes.fr/tel-00320012.
Texto completoEnaux, Christophe. "Essai de modelisation spatio-temporelle des flux de deplacements de travail exemple de la region urbaine strasbourgeoise de 1975 a 1990". Université Louis Pasteur (Strasbourg) (1971-2008), 1997. http://www.theses.fr/1997STR1GE04.
Texto completoThis study consists in an attempt of spatio-temporal modelisation of the journey-to-work flows. It is based on the main phenomenons contributing to the modification of the journey flows. The model, which is a prototype, thus takes into account the process of junction between work supply and demand, the spatial relocalisation of populations and economic activities, as well as retirement, mortality and occupational mobility. The flows dynamic is generated through the integration of spatial and temporal modelisation tools. The resulting mathematic model has been applied to the strasbourg urban region delimitated by a criteria of the intensity of links between the spatial units of the bas-rhin county. The estimated results of the evolution of the journey-to-work flows on a fifteen-year period seem acceptable. The model "simflux" provides a satisfying spatial interaction estimation between the zones of the studied area. However, some problems can be noticed. It presents a tendency to overestimates the flows between the neighbouring spatial units, whereas it underestimates those between much further zones. Complementary applications and callibrations are necessary to determine the descriptive quality of the journey-to-work flows evolution of the various mechanisms introduced in the model
Bonato, Simon. "Étude de la variabilité spatiale et temporelle des communautés phytoplanctoniques en Manche Orientale - Utilisation de la cytométrie en flux de scanning". Thesis, Littoral, 2015. http://www.theses.fr/2015DUNK0379/document.
Texto completoPhytoplankton micro-organisms play a key role in marine ecosystems as main primary producers, being responsible for most of carbon uptake, but also due to their fast division rates which allow them to effectively react to environmental changes and which make them potentially good bio-indicators. Most previous studies have based their observations on low frequency sampling, only considering one fraction of phytoplankton communities, resulting in a significant loss of information on the dynamics of phytoplankton abundance and diversity. This thesis was carried out in the frame of the European cross-border DYMAPHY project, which main objective was to improve the understanding and the evaluation of the quality of marine waters in the English Channel and the North Sea, through the study of the whole phytoplankton compartment and related environmental parameters. A high frequency and/or high resolution approach, through the use of semi-automated flow cytometry, allowed us to reduce this loss of information and to better characterize the phytoplankton spatial and temporal variability in coastal water of the eastern English Channel.Three approaches were applied, leading to the ollowing results : (i) A high frequency study, performing one analysis every 10 minutes, which revealed a strong phytoplankton variability at the regional scale, with community assemblages that were not governed by hydrology ; (ii) A seasonal monitoring of the whole phytoplankton size-spectrum, which revealed the seasonal successions and the main factors governing them : nutrient concentrations and the daily light level which structured the transition of most phytoplankton groups ; (iii) A three-year follow-up at a coastal station, which made it possible to relate the traits-based characterization of each functional phytoplankton group to the environmental conditions, in order to better understand phytoplankton community assembly in response to environmental variability. The results have revealed a functional differentiation mainly due to the use of resources and the growth strategies, both of them driven by a resource gradient. This study confirms the importance of the "mass ration hypothesis", which predicts that the dominant life traits of the most abundant species, would be the main driver of the key ecosystem processes
Mengual, Baptiste. "Variabilité spatio-temporelle des flux sédimentaires dans le Golfe de Gascogne : contributions relatives des forçages climatiques et des activités de chalutage". Thesis, Brest, 2016. http://www.theses.fr/2016BRES0109/document.
Texto completoThe spatio-temporal variability of sediment fluxes under the influence of natural forcings and trawling activities was assessed at the scale of the Bay of Biscay shelf, from in situ data and a 3D process-based numerical modelling. Two sea trials were carried out to quantify physical impacts induced by a professional trawling gear over an intensively trawled area of the shelf, the "Grande-Vasière", in terms of resuspension (turbid plume) and alteration of the surficial sediment nature and structure. These data enabled to estimate an average trawling-induced erosion rate of 0.13 kg.m-2. Their combination with fishing effort data led to monthly spatial distributions of trawling-induced erosion fluxes.Besides, a 3D realistic hydro-sedimentary model has been set up and calibrated from measurements acquired at a mooring station. The calibration task mainly consisted in assessing the natural erosion law setting under the influence of waves and currents. A new formulation of the erosion law has been proposed to describe the erosion of any mixture of mud and fine sand (sediment facies classically encountered on continental shelves) and led to a noteworthy improvement of the model response in terms of turbidity. Two 5-year simulations were performed accounting for natural forcings only or both natural and anthropogenic forcings in order to quantify and compare their respective contributions to sediment fluxes (vertical and horizontal sediment dynamics). The temporal variability of sediment fluxes is described in a succession of typical regimes occurring in response to various conditions of forcings (e.g. tide, wind, wave, trawling), and residual fluxes are assessed at seasonal and annual scales: without accounting for riverine sediment inputs, the mud flux is estimated to 1.6 Mt/yr outflowing northward (at the latitude of the Pointe du Raz) and to 0.62 Mt/yr toward the continental slope (through the 180 m isobath)
Dencausse, Guillaume. "Échanges indo-atlantiques d’eau subtropicale en relation aux structures frontales et de mésoéchelle : utilisation de la série temporelle altimétrique de niveau de la mer". Brest, 2009. http://www.theses.fr/2009BRES2051.
Texto completoIndo-Atlantic exchanges of subtropical water play a crucial role in controlling global climate. The intense mesoscale activity south of Africa contributes to these exchanges, yet remains poorly described. A commonly accepted circulation scheme of those waters assmues that the subtropical gyres of the neighbouring oceans are partially connected, forming a super-gyre. Using an altimeter-derived sea-level time series spanning over 12 years, we study the exchanges through the “northern branch” of the super-gyre (Indian to Atlantic ocean), and through the “southern branch” (opposite direction). Regarding the northern branch, an initial study of the Agulhas Current Retroflection yields a statistical description of its behaviour, and shows the disrupting role of local bathymetry. Then, a thorough tracking of all Agulhas Rings trajectories shed by the Retroflection yields 3 typical paths, linked to regional bathymetry, whose contributions to inter-ocean exchanges are evaluated. Applying the same methods to regional simulations shows inadequate behaviour of the Retroflection and ring trajectories. Exchanges through the southern branch of the super-gyre could be associated with the a jet-like flow of the Subtropical Front, the question of its continuity thus being crucial. If the front seems continuous in the mean sea level field, applying the method developed to locate the mean front to weekly SSH fields shows that mesoscale features west of the retroflection strongly disturb its path, making it discontinuous. Exchanges mechanisms through this branch are thus probably more complex
Renard, Xavier. "Time series representation for classification : a motif-based approach". Thesis, Paris 6, 2017. http://www.theses.fr/2017PA066593/document.
Texto completoOur research described in this thesis is about the learning of a motif-based representation from time series to perform automatic classification. Meaningful information in time series can be encoded across time through trends, shapes or subsequences usually with distortions. Approaches have been developed to overcome these issues often paying the price of high computational complexity. Among these techniques, it is worth pointing out distance measures and time series representations. We focus on the representation of the information contained in the time series. We propose a framework to generate a new time series representation to perform classical feature-based classification based on the discovery of discriminant sets of time series subsequences (motifs). This framework proposes to transform a set of time series into a feature space, using subsequences enumerated from the time series, distance measures and aggregation functions. One particular instance of this framework is the well-known shapelet approach. The potential drawback of such an approach is the large number of subsequences to enumerate, inducing a very large feature space and a very high computational complexity. We show that most subsequences in a time series dataset are redundant. Therefore, a random sampling can be used to generate a very small fraction of the exhaustive set of subsequences, preserving the necessary information for classification and thus generating a much smaller feature space compatible with common machine learning algorithms with tractable computations. We also demonstrate that the number of subsequences to draw is not linked to the number of instances in the training set, which guarantees the scalability of the approach. The combination of the latter in the context of our framework enables us to take advantage of advanced techniques (such as multivariate feature selection techniques) to discover richer motif-based time series representations for classification, for example by taking into account the relationships between the subsequences. These theoretical results have been extensively tested on more than one hundred classical benchmarks of the literature with univariate and multivariate time series. Moreover, since this research has been conducted in the context of an industrial research agreement (CIFRE) with Arcelormittal, our work has been applied to the detection of defective steel products based on production line's sensor measurements
Gernez, Pierre. "Analyse de la variabilité temporelle des propriétés optiques en mer Ligure depuis un moiullage instrumenté (site Boussole) : fluctuations à haute fréquence, cyclicité diurne, changements saisonniers et variabilité interannuelle". Paris 6, 2009. http://www.theses.fr/2009PA066644.
Texto completoRenard, Xavier. "Time series representation for classification : a motif-based approach". Electronic Thesis or Diss., Paris 6, 2017. http://www.theses.fr/2017PA066593.
Texto completoOur research described in this thesis is about the learning of a motif-based representation from time series to perform automatic classification. Meaningful information in time series can be encoded across time through trends, shapes or subsequences usually with distortions. Approaches have been developed to overcome these issues often paying the price of high computational complexity. Among these techniques, it is worth pointing out distance measures and time series representations. We focus on the representation of the information contained in the time series. We propose a framework to generate a new time series representation to perform classical feature-based classification based on the discovery of discriminant sets of time series subsequences (motifs). This framework proposes to transform a set of time series into a feature space, using subsequences enumerated from the time series, distance measures and aggregation functions. One particular instance of this framework is the well-known shapelet approach. The potential drawback of such an approach is the large number of subsequences to enumerate, inducing a very large feature space and a very high computational complexity. We show that most subsequences in a time series dataset are redundant. Therefore, a random sampling can be used to generate a very small fraction of the exhaustive set of subsequences, preserving the necessary information for classification and thus generating a much smaller feature space compatible with common machine learning algorithms with tractable computations. We also demonstrate that the number of subsequences to draw is not linked to the number of instances in the training set, which guarantees the scalability of the approach. The combination of the latter in the context of our framework enables us to take advantage of advanced techniques (such as multivariate feature selection techniques) to discover richer motif-based time series representations for classification, for example by taking into account the relationships between the subsequences. These theoretical results have been extensively tested on more than one hundred classical benchmarks of the literature with univariate and multivariate time series. Moreover, since this research has been conducted in the context of an industrial research agreement (CIFRE) with Arcelormittal, our work has been applied to the detection of defective steel products based on production line's sensor measurements
Eloire, Damien. "Spatial and temporal patterns of plankton in European coastal waters : analysis and comparison of zooplankton time series". Thesis, Montpellier 2, 2010. http://www.theses.fr/2010MON20059.
Texto completoClimate change is unequivocal and dramatic changes are under way in the world's oceans. Long-term observations of indicators such as plankton can provide a better understanding of these changes. Considerable efforts have been made to monitor plankton in European coastal waters and have produced a large amount of datasets yet to be fully exploited. Analytic tools were first developed to solve taxonomic discrepancies in datasets and for temporal analyses. Time series analysis of plankton at L4 from 1988 to 2007 reveals profound changes in the composition of the spring and autumn phytoplankton blooms, and long-term variations in abundance of the dominant zooplankton taxa. Phytoplankton is driving the seasonal succession of meroplanktonic larvae. Changes in sea surface temperature and wind conditions control temporal patterns of plankton communities. Spatio-temporal patterns of zooplankton are compared at 4 sites: Ston (northern North Sea), L4 (wes tern English Channel), MC (Tyrrhenian Sea), and C1 (Adriatic Sea) from 1998 to 2007. The communities structure is on average stable and seasonal variations are the main source of long-term variability. Chlorophyll a and wind are responsible for the community patterns observed at Ston and L4 whereas temperature is the main driver at MC and C1. This study supports evidences of the extreme flexibility of zooplankton communities in adjusting to a variable environment. We highlighted the importance of factors such as taxonomy and temporal scale on time series analysis, and the necessity of maintaining long-term series to monitor future changes in the context of climate change
Vongvixay, Amphone. "Mesure et analyse de la dynamique temporelle des flux solides dans les petits bassins versants : cas d'un bassin versant agricole en région d'élevage (basse-Normandie, France)". Phd thesis, Rennes, INSA, 2012. https://tel.archives-ouvertes.fr/tel-00688884.
Texto completoThe study was performed on the Moulinet and the Oir streams watershed, in Lower-Normandie region. The watershed area is 4,53 km2 and 87 km2 respectively. The main objectives are: 1) to measure and describe the temporal dynamics of the SSC, and 2) to relate these dynamics with the SS origins, the climatic determinants and the stream's order. The measuring of bed-load premises to determine the criterion for mobilizing particles from stream's bottom. The measurement of suspended sediment concentration (SSC) through the water turbidity was deepened. The SSC temporal dynamics was analyzed by different approaches: relationship SSC-discharge, statistic analysis and modeling with different time scale (year, month, season, day and flood scale). A first comparison of the hydrological response between the catchment of Moulinet and the Oir was presented
Ndiade, Bourobou Dyana. "Dynamique spatiale et temporelle de la diversité génétique d’une espèce rare en Afrique Centrale : baillonella toxisperma Pierre (le Moabi)". Thesis, Montpellier 2, 2011. http://www.theses.fr/2011MON20045/document.
Texto completoIf genetic diversity patterns of gregarious rainforest forest trees are well known, few knowledges are available about low density tree species. Does those last one follow the same genetic distribution pattern? Which biotic and abiotic factors underline the spatial structure and evolution of the genetic diversity of such species? In order to improve the knowledge of the biology of such species, we have propose through nuclear microsatellite(nuc) and chlorosplastic (cp) markers to (i) analyse the reproductive system of a low density tree species, (ii) assess its dispersal capacity through seeds and pollen, and finally to (iii) describe the spatial genetic structure at a fine and large scale. We have addressed those questions with Baillonella toxisperma Pierre (commonly named Moabi), a commercial tree of many uses, known to be rare (1 ind/15ha à 20 ha) and distributed through different ecologicals areas of Congo basin. Three main results rise from our study: (i) Despite a strong isolation of the adults, B. toxisperma has a dominant allogamous reproductive system (tm ≈ 98%) with a reduce rate of self-pollination (1- tm< 3%) which is probably due to occurrence of protandry. (ii) As expected in the case of low density trees, the spatial statistic (Sp) of the fine spatial genetic structure is very low [Spnuc = 0.003 ; Spcp = 0.015]. Those reflected a very high gene flow mediated through pollen [σp = 9.8 km à 10.8 km] and seeds [σs = 4.0 km à 6.3 km], that probably mediated by efficient dispersal vectors like bats, human and elephant. At a large scale, a phylogenetic signal has been detected between individuals located in both side of the thermic equator, mainly between those from the block forest of Cameroon and Gabon [RST = 0.313 > RSTp = 0.115, P < 0.001]. Two discretes genetics units from the Gabon block forest which separate individuals of the West coastal forests from the lowland forest ones (in the inland) have also been detected and showed a moderate genetic differentiation [FST = 0.068, P < 0.001]. The genetic differentiation between these three units could be explained by a geographical isolation during past climatic disturbances in the African rainforest, occurred in the Pleistocene and Holocene, and which will be still maintained up to date by a reproductive isolation caused by flowering asynchrony periods among individuals. The occurrence of these three genetic units suggests a biogeographical repartition of B. toxisperma in the Congo basin that is mainly due to the past and current climate. Our conclusions may lead to implement conservation strategies and sustainable management programm for biodiversity in Central Africa
Boissinot, Stéphane. "Phylogénie d'allèles et flux géniques dans les populations naturelles : variabilité de l'ADN mitochondrial et du chromosome Y chez la souris domestique". Montpellier 2, 1994. http://www.theses.fr/1994MON20199.
Texto completoArdon, Jean. "Modélisation probabiliste de la dépendance spatiale et temporelle appliquée à l’étude du péril sécheresse dans le cadre du régime français d’indemnisation des catastrophes naturelles". Thesis, La Rochelle, 2014. http://www.theses.fr/2014LAROS002.
Texto completoThis work was performed at CCR, a French reinsurance company, within the studies that are conducted to model natural disasters, and particularly the drought hazard. Drought is the word used to denote the shrink-swell clay phenomenon that damages individual houses. These researches are related to an internal model that estimates the annual cost of a drought. This model crosses insurance data and soil moisture data to evaluate the cost of a occured event. CCR wants this model to be improved towards a probabilistic version by conceiving a generator of drought events that have to be realistic, although they are fictive. This generator will allow the estimation of the probability distribution of the drought cost. In order to conceive a fictive event generator for CCR’s drought model, mathematical tools have been used to model dependence between spatio-temporal random variables. The chosen method consists of studying and modeling separately spatial dependence and temporal dependence. Temporal dependence is modelized with time series models such as classical decomposition and autoregressive processes. Spatial dependence is modelized with kriging and copula theory. Spatial random noise is generated with a copula and then time series models are applied to rebuild original process. Kriging is used when generated data need to be interpolated, for example when data are generated only on a subset of the main grid. Results of the generator exploitation are given. They will be used by CCR for provisionning and pricing. These results will also be used for the estimation of the two-hundred-year cost of natural disasters within the new European Solvency II Directive
Leleu, Thomas. "Variabilité spatio-temporelle de la composition des fluides hydrothermaux (observatoire fond de mer EMSO-Açores, Lucky Strike) : traçage de la circulation hydrothermale et quantification des flux chimiques associés". Thesis, Toulouse 3, 2017. http://www.theses.fr/2017TOU30023/document.
Texto completoThis thesis present a detailed study of the composition of high temperature fluid from the Lucky Strike hydrothermal field (37°N, Mid Ocean Ridge) collected during three sampling campaigns within the framework of the deep sea observatory EMSO-Azores. The hydrothermal field has developped around a fossil lava lake framed by three ancient volcanic cones. In 2013, the discovery of a new active site to the East of the system, and presenting an unprecedented fluid composition at Lucky Strike (low Cl concentration and high Fe and Mn concentration), lead to a new model of hydrothermal circulation based on chemical geothermobarometer (Si; Si-Cl) and geothermometer (Fe-Mn) applied to 13 venting sites. We defined 5 groups of sites based on their chlorinity and location around the lava lake. It appears that vapor-dominated Capelinhos fluids were extracted relatively fast from the phase separation zone (estimated at ~2600mbsf). Nevertheless, fluids in the vicinity of the lava lake, both vapor and brine dominated, display P and T conditions of equilibration lower than for Capelinhos fluids. This highlights on-going equilibration process through conductive cooling and/or brine entrainment in the upflow zone up to the layer 2A of the oceanic crust. Chlorinity variations highlight the varying residence time in the upflow of the fluids between vents which depends on physical characteristics of the crust. We studied the temporal variability of fluid composition collected between 2009 and 2015. Two time scales have been evidenced. The first is the sampling scale, i.e. ~1h, and corresponds to subsurface processes indicating that a hydrothermal fluid, conductively cooled (T<150°C), was stored in the porous substratum close to the discharge. The second is at the scale of the year. It shows fluctuations of P and T conditions in the phase separation and different degree of alteration of the substratum in the reaction zone. Intersites variations of Ca/Na ratios (proxies for albitisation) are related to phase separation expected the South Eastern sites that display a more altered substratum. To avoid this issue, we use Li and Sr isotopes which are not affected phase separation. Li concentration and isotopic composition indicates that basalt substratum is relatively fresh with W/R ratio close to 1 calculated for all groups with d7Li of fluid equivalent to substratum. Sr concentration and isotopic composition suggest higher W/R ratio (~7-8) because of seawater Sr partially removed in the recharge. Moreover, other parameters are at play such as secondary mineral formation (albite, anhydrite) during water rock interaction in the greenschist facies. Because the basalt is relatively fresh, the low metal content in the fluid around the lava lake is due to storage, in the subsurface, of approximately ~60-70% of Fe that is mobilized in the reaction zone compared to Fe-Mn rich Capelinhos fluids. Furthermore, the Cl variability from the fluids at Lucky Strike brings a unique opportunity to study the REE distribution from the reaction zone to the discharge into the deep ocean. We show that the LREE are preferentially concentrated into the brine phase. Furthermore, the Eu is linked to the Sr geochemical cycle. Dissolved REE from buoyant plume fluids highlight a scavenging effect. The Nd isotopic compositions indicate redissolution process. This Nd isotopes modification of the deep seawater is similar to the process of "boundary exchange" that occurs at the ocean/continents interface. Considering the global distribution of submarine hydrothermalism, the Nd modification at the ridge could have an impact on the global Nd cycle in the oceans and act as a "ridge exchange"
Fuchs, Robin. "Méthodes neuronales et données mixtes : vers une meilleure résolution spatio-temporelle des écosystèmes marins et du phytoplancton". Electronic Thesis or Diss., Aix-Marseille, 2022. http://www.theses.fr/2022AIXM0295.
Texto completoPhytoplankton are one of the first links in the food web and generate up to 50% of the world's primary production. The study of phytoplankton and their physical environment requires observations with a resolution of less than a day and a kilometer, as well as the consideration of the heterogeneous types of data involved and the spatio-temporal dependency structures of marine ecosystems.This thesis aims to develop statistical methods in this context by using technologies such as automated flow cytometry. Theoretical developments focused on Deep Gaussian Mixture Models (DGMM) introduced by Viroli and McLachlan (2019). To better characterize phytoplankton ecological niches, we extended these models to mixed data (exhibiting continuous and non-continuous variables) often found in oceanography. A clustering method has been proposed as well as an algorithm for generating synthetic mixed data.Regarding the high-frequency study itself, convolutional neural networks have been introduced to process flow cytometry outputs and to study six functional groups of phytoplankton in the littoral zone and the open ocean. Differentiated and reproducible responses of these groups were identified following wind-induced pulse events, highlighting the importance of the coupling between physics and biology. In this regard, a change-point detection method has been proposed to delineate epipelagic and mesopelagic zones, providing a new basis for the calculation of mesopelagic carbon budgets
D'Angelo, Benoît. "Variabialité spatio-temporelle des émissions de GES dans une tourbière à Sphaignes : effets sur le bilan carbone". Thesis, Orléans, 2015. http://www.theses.fr/2015ORLE2058/document.
Texto completoPeatlands cover only 2 to 3% of the land area but store between 10 and 25% of the soil carbon. The outcome of the anthropic and climatic pressure on these ecosystems is uncertain regarding their functions and storage. A better understanding of these ecosystems is needed to determine the factors and their interactions on greenhouse gas (GHG) emission. This work consist in monitoring GHG emissions and controlling factors in a Sphagnum peatland to estimate its carbon balance. Experimentation on mesocosms were carried out to explore the effect of hydrology on the fluxes and a monitoring on 4 sites was made to study the daily variability. Results show that La Guette peatland was a carbon source (-220 ± 33 gC m-2 an-1) in spite of the high water table level. The importance of the spatial variability measured in the site was also demonstrate. The hydrology effect was confirmed by the mesocosms experiments and high water table level shows that gas transport might have an effect. Finally the study of the daily variability show that the temperature sensitivity of the respiration might be different between day and night and that synchronizing soil temperatures and respiration can improve the respiration representation
Benhmida, Saïd. "Robustesse et comportement asymptotique d'un TRA-estimateur des coefficients d'un processus ARMA (p,q)". Nancy 1, 1995. http://www.theses.fr/1995NAN10035.
Texto completoPerrinet, Laurent. "Comment déchiffrer le code impulsionnel de la Vision? Étude du flux parallèle, asynchrone et épars dans le traitement visuel ultra-rapide". Phd thesis, Université Paul Sabatier - Toulouse III, 2003. http://tel.archives-ouvertes.fr/tel-00002693.
Texto completoColombier, Jean-Philippe. "Théorie et simulation de l'interaction des impulsions laser ultracourtes à flux modéré avec un solide métallique". Phd thesis, Université Jean Monnet - Saint-Etienne, 2005. http://tel.archives-ouvertes.fr/tel-00011110.
Texto completoLa mise en mouvement ultrarapide des électrons libres insuffle une dynamique puissante de destruction du métal. Des modèles optiques, thermiques et hydrodynamiques adaptés, réalisant la transition entre l'état dégénéré de la matière condensée vers un régime plasma chaud non-dégénéré, sont ici développés. Nous les avons insérés dans un code Lagrangien de simulation hydrodynamique. Nous montrons que des états thermodynamiques extrêmes, hors d'équilibre, peuvent être engendrés et nous avons comparé les taux d'ablation obtenus aux résultats d'expérience.
Une conductivité électrique hors d'équilibre est également développée afin de rendre compte des effets produits par la dynamique électronique sur les propriétés d'absorption optique. Plusieurs types d'expériences numériques, impliquant notamment des dispositifs pompe-sonde, sont ensuite exposés afin d'améliorer notre compréhension des processus de transport (électron-électron et électron-phonon) dans ce régime. Nous avons enfin appliqué cette modélisation aux effets produits par une impulsion mise en forme temporellement afin d'optimiser les expériences d'ablation.
Boireau, Clémence. "Antibiorésistance en santé animale en France : caractérisation à des fins d’évaluation et de lutte et mises en perspective dans un contexte One Health". Thesis, Lyon, 2019. http://www.theses.fr/2019LYSE1114/document.
Texto completoAntimicrobial resistance is a major and global public health concern. In this context, the research problem was to provide decision support to the risk manager for the implementation and assessment of control measures in animal health. To limit and manage the phenomenon, we must know the dynamic of its evolution: the surveillance is therefore a key element in the fight against antimicrobial resistance. At first, using a population survey and a sociological approach, this research determined to what extent the data collected by the French surveillance network of antimicrobial resistance in diseased animals (RESAPATH) could be used to answer the research problem. Since the representativeness and the coverage of the RESAPATH were considered satisfactory, surveillance data were used to characterize the dynamics of the resistances and generalized additive models were developed. The comparison of resistance trends and control measures underscored the positive impact of changes in practices on the evolution of resistances. Finally, in the context of the ‘One Health’ concept that advocates an integrated and collaborative approach to health, the parallel was drawn between resistances in isolates from animals and humans. Data from the French surveillance network of antimicrobial resistance of bacteria isolated in community (MedQual) were analysed. Resistance dynamics were specific to each species. These results advocate that the efforts to fight antimicrobial resistance must be carried in all sectors and for all species, both in human and veterinary medicine
Willis, Pascal. "DORIS et la géodésie globale". Habilitation à diriger des recherches, Université Pierre et Marie Curie - Paris VI, 2003. http://tel.archives-ouvertes.fr/tel-00423668.
Texto completoPlaud, Angéline. "Classification ensembliste des séries temporelles multivariées basée sur les M-histogrammes et une approche multi-vues". Thesis, Université Clermont Auvergne (2017-2020), 2019. http://www.theses.fr/2019CLFAC047.
Texto completoRecording measurements about various phenomena and exchanging information about it, participate in the emergence of a type of data called time series. Today humongous quantities of those data are often collected. A time series is characterized by numerous points and interactions can be observed between those points. A time series is multivariate when multiple measures are recorded at each timestamp, meaning a point is, in fact, a vector of values. Even if univariate time series, one value at each timestamp, are well-studied and defined, it’s not the case of multivariate one, for which the analysis is still challenging. Indeed, it is not possible to apply directly techniques of classification developed on univariate data to the case of multivariate one. In fact, for this latter, we have to take into consideration the interactions not only between points but also between dimensions. Moreover, in industrial cases, as in Michelin company, the data are big and also of different length in terms of points size composing the series. And this brings a new complexity to deal with during the analysis. None of the current techniques of classifying multivariate time series satisfies the following criteria, which are a low complexity of computation, dealing with variation in the number of points and good classification results. In our approach, we explored a new tool, which has not been applied before for MTS classification, which is called M-histogram. A M-histogram is a visualization tool using M axis to project the density function underlying the data. We have employed it here to produce a new representation of the data, that allows us to bring out the interactions between dimensions. Searching for links between dimensions correspond particularly to a part of learning techniques called multi-view learning. A view is an extraction of dimensions of a dataset, which are of same nature or type. Then the goal is to display the links between the dimensions inside each view in order to classify all the data, using an ensemble classifier. So we propose a multi-view ensemble model to classify multivariate time series. The model creates multiple M-histograms from differents groups of dimensions. Then each view allows us to get a prediction which we can aggregate to get a final prediction. In this thesis, we show that the proposed model allows a fast classification of multivariate time series of different sizes. In particular, we applied it on aMichelin use case