Academic literature on the topic 'Causalité à des horizons multiples'

Horizon picking from sub-bottom profiler (SBP) images has great significance in marine shallow strata studies. However, the mainstream automatic picking methods cannot handle multiples well, and there is a need to set a group of parameters manually. Considering the constant increase in the amount of SBP data and the high efficiency of deep learning (DL), we proposed a physicals-combined DL method to pick the horizons from SBP images. We adopted the DeeplabV3+ net to extract the horizons and multiples from SBP images. We generated a training dataset from the Jiaozhou Bay survey (Shandong, China) and the Zhujiang estuary survey (Guangzhou, China) to increase the applicability of the trained model. After the DL processing, we proposed a simulated Radon transform method to eliminate the surface-related multiples from the prediction by combining the designed pseudo-Radon transform and correlation analysis. We verified the proposed method using actual data (not involved in the training dataset) from Jiaozhou Bay and Zhujiang estuary. The positions of picked horizons are accurate, and multiples are suppressed.

La formation professionnelle connaît un développement important dans les PME françaises, mais ne sera reconnue parles professionnels qu’à condition de pouvoir en évaluer les effets sur la performance de l’organisation. L’exploitation des résultats d’une enquête menée auprès de 180 PME du Sud de la France, au moyen d’une analyse factorielle des correspondances multiples, permet une réflexion sur les relations de causalité entre les différentes politiques de formation et la performance de la PME. Si les PME ayant une politique de formation plus élaborée semblent être également les plus performantes, il convient toutefois de s’interroger sur les caractéristiques générales des PME de l’échantillon.

Summary The Ceará Basin is a deepwater exploration frontier basin that comprises part of the Brazilian equatorial margin. This basin has been receiving renewed attention from the petroleum industry since the discovery of important deepwater oil fields in its African counterpart. However, detailed seismic stratigraphic, depositional, and structural frameworks for the Ceará Basin are still lacking in the literature. We have analyzed a series of 2D seismic data sets and stumbled into the pitfalls of migration artifacts (i.e., multiples) ultimately realizing that reprocessing was the best option to avoid the mistake of interpreting these artifacts as geologic features. Multiples can be difficult to identify in seismic data in which they mimic the true geology of the region, and they often present a pitfall for less experienced interpreters. Indeed, the identification and removal of multiples is crucial because they do not reflect the true geology in the subsurface and may otherwise lead to incorrect business decisions. Geological feature: Stratigraphy of the Ceará Basin, offshore Brazil Seismic appearance: Strong seismic horizons mimicking geological layering Alternative interpretations: Multiples arising from poor seismic migration processing Features with similar appearance: Strong seismic horizons reflecting basement and carbonates Formation: Rift sequence of the Ceará Basin Age: Cretaceous Location: Ceará Basin, offshore Brazil Seismic data: Obtained by the Brazilian National Petroleum Agency and reprocessed by the authors Analysis tool: Reprocessing

This study requires to use a qualitative model, while for the type of research, using Content Analysis. Content analysis is a model used to examine the documentation data in the form of text, images, symbols, and so forth. A research technique for making inferences that can be replicated and valid data with the context. As a technique of research, the content analysis includes specific procedures for processing the scientific data with the aim of providing knowledge, open new horizons and presenting the facts. Assessment of the linkages primes 3 includes a discussion on the relationship with the meaning and also lafadznya, apart from Al-Kautsar consists of three paragraphs, including the font used and unused in the letter, the difference between the two is 6 (multiples of prime numbers 3), for the number of repetitions of letters obtained 111.111.111.123.444.510 numbers (multiples of primes 3), in a letter lafadz هللاproduce numbers 15 and 1,040 (multiples of primes 3), the sequence of letters and the number of letters in the Qur'an produced 114 108 numbers (multiples of primes 3), correlation beginning and end of the letter gives the figure 1.515 (multiples of primes 3), and the number of repetitions of letters in each verse, second verse generate numbers 1.111.111.224, 1.111.111.122 generate numbers second paragraph, and paragraph the third 1.111.111.125 produce numbers which are all multiples of primes 3.

Subbasalt imaging for hydrocarbon exploration faces challenges with the presence of multiple scattering, attenuation, and mode conversion as seismic waves encounter highly heterogeneous and rugose basalt layers. A combination of modern seismic acquisition that can record densely sampled data and advanced imaging techniques make imaging through basalt feasible. Yet, the internal multiples, if not properly handled during seismic processing, can be mapped to reservoir layers by conventional imaging methods, misguiding geologic interpretation. Traditional internal multiple elimination methods suffer from the requirement of picking horizons of multiple generators and/or a top-down adaptive subtraction process. Marchenko imaging provides an alternative solution to directly remove the artifacts due to internal multiples, without the need of horizon picking or subtraction. In this paper, we evaluate a successful application of direct Marchenko imaging for subbasalt demultiple and imaging with an offshore Brazil field data set. The internal multiples in this example are generated from the seabed and basalt layers, causing severe artifacts in conventional seismic images. We have determined that these artifacts are largely suppressed with Marchenko imaging, and we have developed a general workflow for data preprocessing and regularization of marine streamer data sets. We find that horizontally propagating waves also can be reconstructed by the Marchenko method at far offsets.

Iterative substitution of the multidimensional Marchenko equation has been introduced recently to integrate internal multiple reflections in the seismic imaging process. In so-called Marchenko imaging, a macro velocity model of the subsurface is required to meet this objective. The model is used to back-propagate the data during the first iteration and to truncate integrals in time during all successive iterations. In case of an erroneous model, the image will be blurred (akin to conventional imaging) and artifacts may arise from inaccurate integral truncations. However, the scheme is still successful in removing artifacts from internal multiple reflections. Inspired by these observations, we rewrote the Marchenko equation, such that it can be applied early in a processing flow, without the need of a macro velocity model. Instead, we have required an estimate of the two-way traveltime surface of a selected horizon in the subsurface. We have introduced an approximation, such that adaptive subtraction can be applied. As a solution, we obtained a new data set, in which all interactions (primaries and multiples) with the part of the medium above the picked horizon had been eliminated. Unlike various other internal multiple elimination algorithms, the method can be applied at any specified target horizon, without having to resolve for internal multiples from shallower horizons. We successfully applied the method on synthetic data, where limitations were reported due to thin layers, diffraction-like discontinuities, and a finite acquisition aperture. A field data test was also performed, in which the kinematics of the predicted updates were demonstrated to match with internal multiples in the recorded data, but it appeared difficult to subtract them.

Les prix de marché des actifs risqués sont dictés par les actions des agents économiques qui ont des horizons d'investissement différents: ils ajustent leurs portefeuilles à des fréquences différentes et observent les rendements à différentes échelles. Dans cette thèse, nous examinons trois aspects distincts du problème des horizons multiples d'investissement. En premier lieu, nous étudions les implications théoriques de l'hétérogénéité des horizons de décision des investisseurs pour la dynamique des prix. Cette analyse est effectuée dans le cadre d'une rationalité complète et bornée. Deuxièmement, nous testons la capacité de différents modèles de séries chronologiques de volatilité des prix à représenter les propriétés des rendements boursiers simultanément à différentes échelles de temps. Enfin, nous proposons une méthode de mesure de la volatilité à échelle multiple basée sur des filtres d'ondelettes, avec application à la détection des crises financières.

This thesis investigates if Environmental, Social and Governance (ESG) investments can be considered as an independent asset class. As ESG and responsible investing has increased substantially in recent years, responsible investments have entered the portfolios with other asset classes too. Therefore, there is a need in studying ESG investment properties with other financial asset classes. By collecting daily price data from October 2007 to December 2018, we research the directionalities between ESG, ethical, conventional, commodities and currency. Initially, we employed a MODWT, multiscale investment horizon wavelet analysis transformation of the data. The decomposed wavelet data is then applied in pairwise linear and non-linear Granger causality estimations to study the directionality relationships dependent on investment horizon. Additionally, econometric filtering processes have been employed to study the effects of volatility on directionality relationships. The results mainly suggest significant directionality relationships between ESG and the other asset classes. On the medium-term investment horizon, almost all estimations indicate strict bidirectionality. Thus, on the medium-term, ESG can be said to be integrated with the other asset classes. For the long-term horizon, most relationships are still predominantly bidirectional between ESG and all other asset classes. The biggest differences are found on the short-term horizon, with no directionality found between ESG and commodities that cannot be explained by volatility. Furthermore, most directionality relationships also disappear when controlling for the volatility transmission between ESG and currency on the short-term horizon. Thus, our findings suggest significantly more integration between ESG and ethical and conventional as bidirectionality overwhelmingly prevails regardless of investment horizon. As previous research has found similarities between ethical and conventional as well as ESG having similar characteristics to commodities as conventional and ethical, we suggest that ESG should be considered as being integrated and having strong similarities with other equities. Thus, it should be treated as being part of the conventional equity asset class. Deviations from bidirectionality could be caused by ESG variable specific heterogeneity. However, despite our rejection of ESG as an independent asset class, it still carries significant potential as it excludes firms with climate-harming practices, thereby helping in combating climate-related as well as social and governance issues the world is facing.

Modalités de gestion du milieu temporel dans une conduite de processus multiples en situation dynamique :une recherche dans des entreprises horticoles. Cette recherche porte sur les modalités de gestion temporelle, dans des situations professionnelles tendues entre les nécessités d'une production engageant des phénomènes dynamiques multiples et une rationalisation du travail supposée faire face aux besoins économiques de l'entreprise, en l'occurrence, dans le secteur de l'horticulture. La thèse soutenue est que les travailleurs, et en particulier des chefs de culture en tant qu'encadrants intermédiaires, assurent une gestion de leur milieu temporel de travail, dans la dynamique de leur activité. Cette gestion est active dans le sens où elle intègre des cadres temporels. Ceux-ci peuvent être analysés à la fois comme des ressources et des contraintes dans leur activité. La gestion du milieu temporel peut être entravée par certaines configurations de ces cadres, qui ne permettent pas aux chefs de culture d'intégrer les risques pour la production, pour eux-mêmes ou pour les autres travailleurs. Nous proposons une structure de formalisation des cadres temporels et de leurs interrelations dans la dynamique du milieu temporel. Elle est issue d'une démarche de " dépliage " des temporalités, fondée sur une analyse ergonomique de l'activité. La modélisation des cadres et de la gestion du milieu temporel est une conceptualisation fonctionnelle pour analyser les conditions temporelles du travail en tant que ressources pour un agir temporel pragmatique dans l'activité.

L'analyse de médiation causale est une méthode statistique permettant d'étudier les mécanismes définissant les relations entre trois entités, la première étant une cause, la deuxième une variable de réponse et la troisième un ensemble de variables intermédiaires, aussi appelés médiateurs. Cette approche est devenue populaire dans différents domaines tels que les biostatistiques, l'épidémiologie et les sciences sociales. Son objectif est de décomposer et quantifier l'effet total d'une cause T sur une variable de réponse Y en un effet direct et un effet indirect à travers le(s)médiateur(s) Mi. Dans un diagramme causal ainsi défini peuvent intervenir des covariables mesurées ou non ayant des effets sur les trois variables T, Y et Mi. Quand plusieurs médiateurs sont impliqués dans le modèle de médiation, il y a trois cas possibles de relation entre ces médiateurs : 1) Les médiateurs sont indépendants conditionnellement au traitement et aux covariables mesurées. 2) Les médiateurs sont dépendants conditionnellement au traitement et aux covariables mesurées sans pour autant que l'un affecte l'autre. 3) Les médiateurs sont liés de façon causale, c'est-à-dire que l'un affecte l'autre. Les contributions de cette thèse portent sur les deux premières configurations. Plus particulièrement, l'état de l'art pour l'estimation des effets indirects individuels des médiateurs est de faire plusieurs analyses de médiation simple en parallèle, un médiateur à la fois. Cette approche conduit à une estimation biaisée de l'effet direct et n'est pas justifiée dans la situation 2) car l'hypothèse nécessaire d'Ignorabilité Séquentielle n'est alors pas vérifiée. Le premier chapitre de la thèse propose de résoudre ce problème par l'estimation de la loi multivariée des médiateurs conditionnellement au traitement et décrit les nouvelles hypothèses sous lesquelles une telle approche est valide. Une méthode d'estimation de l'effet direct et de tous les effets indirects individuels est développée, prenant en compte la corrélation entre les médiateurs. Le second chapitre est dédié à l'analyse de médiation multiple2/6dans le cas où le nombre de médiateurs grandit. Deux stratégies sont explorées. La première repose sur une classification spectrale des médiateurs en blocs indépendants, chaque bloc pouvant être analysé avec l'approche précédente. La seconde, applicable dans des problèmes de grande dimension, repose sur la sélection de médiateurs potentiels à l'aide d'une approche de type Group-LASSO en amont de l'analyse de médiation. Le troisième chapitre présente le packageR multimediate où les trois méthodes précédentes sont implémentées. On y présente l'algorithme d'estimation en fonction des différents types de médiateurs considérés (linéaires, binaires et catégoriels). Le dernier chapitre présente des applications sur des données réelles. D'une part une application en épidémiologie pour quantifier et décomposer l'effet de la thérapie hormonal sur le cancer du sein. D'autre part une application en psychiatrie, où nous analysons les effets des tempéraments affectifs sur l'anorexie mentale
Causal mediation analysis is a statistical method used to study the mechanisms defining the relationships between three entities, the first being a cause, the second a response variable and the third a set of intermediate variables, also called mediators. This approach has become popular in various domains such as biostatistics, epidemiology and social sciences. The goal of such an analysis is to decompose and quantify the total effect of a cause T on a outcome Y into a direct effect and an indirect effect through the mediator(s) Mi. In a causal diagram defined in this way, measured or unmeasured covariates can intervene with effects on the three variables T, Yand Mi .When several mediators are involved in the mediation model, there are three possible situations:1) The mediators are independent conditionally on the treatment and on the measured covariates.2) Mediators are conditionally dependent on the treatment and on the measured covariates but this dependence is not of causal nature (i.e. mediators do not cause each other).3) Mediators are causally related, that is, one affects the other.The contributions of this thesis focus on the first two configurations. More particularly, the state of the art for estimating the individual indirect effects of mediators isto perform several simple mediation analyzes in parallel, one mediator at a time. This approach leads to a biased estimate of the direct effect and is not justified in situation 2) because the necessary assumption of Sequential Ignorability is then not verified.The first chapter of the thesis proposes to solve this problem by estimating the multivariate distribution of mediators conditional on the treatment and describes the new hypotheses under which such an approach is valid. A method for estimating the direct effect and all individual indirect effects is developed, taking into account the correlation between the mediators. The second chapter is dedicated to the analysis of multiple mediation in the case where the numberof mediators grows. Two strategies are explored. The first is based on a spectral classification of mediators into independent blocks, each block can be analyzed with the previous approach. The second strategy, applicable in large-scale problems, is based on the selection of potential mediators using a Group-LASSO type approach upstream of the mediation analysis. The third chapter presents the R multimediate package where the three previous methods are implemented. We present the estimation algorithm according to the different types of mediators considered (linear, binary and categorical). The last chapter presents applications on real data.On the one hand, I illustrate an application in epidemiology to quantify and disentangling the effect of hormonal therapy on breast cancer. On the other hand, I present an application in psychiatry, where I analyze the effects of affective temperaments on anorexia nervosa