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La psychanalyse est-elle épistémologiquement dans l’impasse ? Les «Japonais» (Lacan) ou encore les Arabes ne sont-ils pas «psychanalysables» ? Ce sont deux malaises qui ont concomitamment motivé cette recherche. Celle-ci découvre alors la «psychanalyse du lien» à laquelle elle suppose un potentiel de résolution de la double crise de la psychanalyse : celle qui lui est intrinsèque et a trait à sa longévité et celle de la rencontre entre cette dernière et des champs opérationnels d’accueil. Analyser les liens plutôt que des sujets en lien révolutionne la métapsychologie classique en la décentrant du pur intrapsychique, lénifiant ainsi son panindividualisme et promettant une «rencontre équitable» entre la psychanalyse et son terrain d’accueil, le tunisien en l’occurrence. La pratique de ce paradigme auprès de couples et de familles tunisiens en situations de recherche et de consultation, alternant au besoin, entretiens individuel, de couple et de famille, génosociogramme commenté, FAT ou encore TAT, permet de déceler des configurations liennaires récurrentes et caractéristiques colorant, par l’Instance culturelle (Kaës, 1998), l’espace du lien. Sont alors identifiés et définis les Objets-reliques, la Co-maternité et le Bel-Oedipe comme émergents du contexte informant respectivement sur les liens généalogique, parento-filial et de couple. C’est ainsi qu’une psychanalyse des liens de couple et de famille ouvre la voie à une lecture conjointe de trois espaces intra, inter et transsubjectif où le travail de subjectivation «se déroule» en même temps qu’elle incite à s’interroger sur les liens, leur nouage et défaillances aux prises avec le contexte culturel. / Is psychoanalysis epistemologically deadlocked? Aren’t the "Japanese" (Lacan) or the Arabs "psychoanalysable"? These are two discomforts that simultaneously motivated this research. It found out the "link psychoanalysis" in which it supposes a potential to resolve the double crisis of psychoanalysis: the intrinsic one related to its longevity and that of the encounter between the latter and the operational hosting fields. Analysing the link rather than subjects in link revolutionized classical metapsychology by offsetting the pure intrapsychic thus soothing its panindividualism and promising an « equitable encounter » between psychoanalysis and its host ground, the Tunisian one in this case. The practice of this « paradigm » with tunisian couples and families in contexts of research and consultation, alternating, on need, individual, couple and family interviews, commented genosociograms, FAT or TAT allowed to detect recurrent and characteristic link configurations, in which Cultural Instance (Kaës, 1998) colours neatly the link space. Thus, could be identified and defined the Relic objects, Co-motherhood and Oedipus-in-law as context emergents informing respectively about genealogical, parental-filial and couple links. That is how a couple and family link psychoanalysis paves the way to a joint reading of three spaces: intra, inter and transsubjective where the subjectivation work occurs. At the same time, it raises questions about link-knitting and failures dealing with the cultural context.

Prostate cancer is one of the most common types of cancer occurring in men. Several types of research have been done using deep learning methods for the classification/prediction of cancer grades. In this thesis, the results of prostate cancer risk prediction, based only on the images of cells from the prostate tissues, have been analyzed. Cell images from the prostate tissues were extracted using a deep learning based segmentation model. These cell images were then used in a Multiple Instance Learning model for cancer risk prediction. An attention mechanism was used to visualize the regions in the tissue to which the model paid more attention. The results suggest that the Multiple Instance Learning (MIL) model achieves an Area Under the receiver Operating Characteristics (AUROC) of 0.641 ± 0.013, which is better than a random model for low-risk vs. high-risk cancer prediction. The model’s prediction was made on cell images, with the glandular information destroyed. The MIL model, however, performs worse than a model which gets to see the glandular architecture of the cells in the prostate tissues. / Prostatacancer är en av de vanligaste typerna av cancer som förekommer ho smän. Flera typer av forskning har gjorts med metoder för djupinlärning förklassificering/förutsägelse av cancerns malignitetsgrad. I detta examensarbete harresultaten av prostatacancerriskprediktion, baserad enbart på bilder av celler från prostatavävnaderna, analyserats. Cellbilder från prostatavävnaderna extraherades med hjälp av en djupinlärningsbaserad segmenteringsmodell. Dessa cellbilder användes sedan i en Multiple Instance Learning-modell för förutsägelse av cancerrisk. En uppmärksamhetsmekanism användes för att visualisera de regioner i vävnaden som modellen ägnade mer uppmärksamhet åt. Resultaten tyder på att Multiple Instance Learning-modellen uppnår en AUROC på 0.641 ± 0.013, vilket är bättre än en slumpmässig modell för förutsägelse av lågrisk kontra högrisk cancer. Modellens förutsägelse gjordes på cellbilder, med körtelinformationen förstörd. MIL-modellen presterar dock sämre än en modell som får se körtelarkitekturen hos cellerna i prostatavävnaderna.

<div>Latency is regarded as the Achilles heel of cloud computing. Pricing is an essential component in the cloud market since it not only directly affects a cloud service provider's (CSP's) revenue but also a user's budget. This dissertation investigates the latency-aware pricing schemes that provide rigorous performance guarantees for the cloud market. The research is conducted along the following major problems as summarized below:</div><div><br></div><div>First, we will address a major challenge confronting the CSPs utilizing a tiered storage (with cold storage and hot storage) architecture - how to maximize their overall profit over a variety of storage tiers that offer distinct characteristics, as well as file placement and access request scheduling policies. To this end, we propose a scheme where the CSP offers a two-stage auction process for (a) requesting storage capacity, and (b) requesting accesses with latency requirements. Our two-stage bidding scheme provides a hybrid storage and access optimization framework with the objective of maximizing the CSP's total net profit over four dimensions: file acceptance decision, placement of accepted files, file access decision and access request scheduling policy. The proposed optimization is a mixed-integer nonlinear program that is hard to solve. We propose an efficient heuristic to relax the integer optimization and to solve the resulting nonlinear stochastic programs. The algorithm is evaluated under different scenarios and with different storage system parameters, and insightful numerical results are reported by comparing the proposed approach with other profit-maximization models. We see a profit increase of over 60% of our proposed method compared to other schemes in certain simulation scenarios.</div><div><br></div><div>Second, we will resolve one of the challenges when using Amazon Web Services (AWS). Amazon Elastic Compute Cloud (EC2) provides two most popular pricing schemes--i) the costly on-demand instance where the job is guaranteed to be completed, and ii) the cheap spot instance where a job may be interrupted. We consider a user can select a combination of on-demand and spot instances to finish a task. Thus he needs to find the optimal bidding price for the spot-instance, and the portion of the job to be run on the on-demand instance. We formulate the problem as an optimization problem and seek to find the optimal solution. We consider three bidding strategies: one-time requests with expected guarantee, one-time requests with penalty for incomplete job and violating the deadline, and persistent requests. Even without a penalty on incomplete jobs, the optimization problem turns out to be non-convex. Nevertheless, we show that the portion of the job to be run on the on-demand instance is at most half. If the job has a higher execution time or smaller deadline, the bidding price is higher and vice versa. Additionally, the user never selects the on-demand instance if the execution time is smaller than the deadline. The numerical results illustrate the sensitivity of the effective portfolio to several of the parameters involved in the model. Our empirical analysis on the Amazon EC2 data shows that our strategies can be employed on the real instances, where the expected total cost of the proposed scheme decreases over 45% compared to the baseline strategy.<br></div>

Business process models are abstractions of concrete operational procedures that occur in the daily business of organizations. To cope with the complexity of these models, business process model abstraction has been introduced recently. Its goal is to derive from a detailed process model several abstract models that provide a high-level understanding of the process. While techniques for constructing abstract models are reported in the literature, little is known about the relationships between process instances and abstract models. In this paper we show how the state of an abstract activity can be calculated from the states of related, detailed process activities as they happen. The approach uses activity state propagation. With state uniqueness and state transition correctness we introduce formal properties that improve the understanding of state propagation. Algorithms to check these properties are devised. Finally, we use behavioral profiles to identify and classify behavioral inconsistencies in abstract process models that might occur, once activity state propagation is used. / Geschäftsprozessmodelle sind Abstraktionen konkreter operationaler Vorgänge, die im täglichen Geschäftsablauf von Organisationen auftreten. Um die Komplexität solcher Modelle zu bewältigen, wurde die Geschäftsprozessmodelabstraktion eingeführt. Ziel ist dabei, von einem detaillierten Prozessmodel mehrere abstrakte Modelle abzuleiten, um so auf einer höheren Abstraktionsstufe ein Verständnis für den Prozess zu bekommen. Während viel in der Literatur über Techniken zur Konstruktion abstrakter Modelle berichtet wurde, ist wenig über die Beziehungen zwischen Prozessinstanzen und abstrakten Modellen bekannt. In dieser Arbeit zeigen wir, wie der Zustand einer abstrakten Aktivität aus den Zuständen ihrer entsprechenden detaillierten Prozessaktivitäten zur Laufzeit berechnet werden kann. Der Ansatz basiert dabei auf der Übertragung des Aktivitätszustands. Mit der Zustandseindeutigkeit und der Korrektheit der Zustandstransitionen führen wir formale Kriterien ein, die das Verständnis der Zustandsübertragung erleichtern. Zudem sind Algorithmen entwickelt worden, um diese Kriterien zu überprüfen. Außerdem nutzen wir Verhaltensprofile um Inkonsistenzen im Verhalten abstrakter Prozessmodelle zu identifizieren und zu klassifizieren, die auftreten können, wenn die Aktivitätszustände gemäß den Regeln abgebildet werden.

With the continuous expansion of data availability in many large-scale, complex, and networked systems, such as surveillance, security, the Internet, and finance, it becomes critical to advance the fundamental understanding of knowledge discovery and analysis from raw data to support decision-making processes. Existing knowledge discovery and data analyzing techniques have shown great success in many real-world applications such as applying Automatic Target Recognition (ATR) methods to detect targets of interest in imagery, drug activity prediction, computer vision recognition, and so on. Among these techniques, Multiple-Instance (MI) learning is different from standard classification since it uses a set of bags containing many instances as input. The instances in each bag are not labeled | instead the bags themselves are labeled. In this area many researchers have accomplished a lot of work and made a lot of progress. However, there still exist some areas which are not covered. In this thesis, we focus on two topics of MI learning: (1) Investigating the relationship between MI learning and other multiple pattern learning methods, which include multi-view learning, data fusion method and multi-kernel SVM. (2) Dealing with the class imbalance problem of MI learning. In the first topic, three different learning frameworks will be presented for general MI learning. The first uses multiple view approaches to deal with MI problem, the second is a data fusion framework, and the third framework, which is an extension of the first framework, uses multiple-kernel SVM. Experimental results show that the approaches presented work well on solving MI problem. The second topic is concerned with the imbalanced MI problem. Here we investigate the performance of learning algorithms in the presence of underrepresented data and severe class distribution skews. For this problem, we propose three solution frameworks: a data re-sampling framework, a cost-sensitive boosting framework and an adaptive instance-weighted boosting SVM (with the name IB_SVM) for MI learning. Experimental results - on both benchmark datasets and application datasets - show that the proposed frameworks are proved to be effective solutions for the imbalanced problem of MI learning.

Les humains sont au coeur de nombreux problèmes de vision par ordinateur, tels que les systèmes de surveillance ou les voitures sans pilote. Ils sont également au centre de la plupart des contenus visuels, pouvant amener à des jeux de données très larges pour l’entraînement de modèles et d’algorithmes. Par ailleurs, si les données stéréoscopiques font l’objet d’études depuis longtemps, ce n’est que récemment que les films 3D sont devenus un succès commercial. Dans cette thèse, nous étudions comment exploiter les données additionnelles issues des films 3D pour les tâches d’analyse des personnes. Nous explorons tout d’abord comment extraire une notion de profondeur à partir des films stéréoscopiques, sous la forme de cartes de disparité. Nous évaluons ensuite à quel point les méthodes de détection de personne et d’estimation de posture peuvent bénéficier de ces informations supplémentaires. En s’appuyant sur la relative facilité de la tâche de détection de personne dans les films 3D, nous développons une méthode pour collecter automatiquement des exemples de personnes dans les films 3D afin d’entraîner un détecteur de personne pour les films non 3D. Nous nous concentrons ensuite sur la segmentation de plusieurs personnes dans les vidéos. Nous proposons tout d’abord une méthode pour segmenter plusieurs personnes dans les films 3D en combinant des informations dérivées des cartes de profondeur avec des informations dérivées d’estimations de posture. Nous formulons ce problème comme un problème d’étiquetage de graphe multi-étiquettes, et notre méthode intègre un modèle des occlusions pour produire une segmentation multi-instance par plan. Après avoir montré l’efficacité et les limitations de cette méthode, nous proposons un second modèle, qui ne repose lui que sur des détections de personne à travers la vidéo, et pas sur des estimations de posture. Nous formulons ce problème comme la minimisation d’un coût quadratique sous contraintes linéaires. Ces contraintes encodent les informations de localisation fournies par les détections de personne. Cette méthode ne nécessite pas d’information de posture ou des cartes de disparité, mais peut facilement intégrer ces signaux supplémentaires. Elle peut également être utilisée pour d’autres classes d’objets. Nous évaluons tous ces aspects et démontrons la performance de cette nouvelle méthode. / People are at the center of many computer vision tasks, such as surveillance systems or self-driving cars. They are also at the center of most visual contents, potentially providing very large datasets for training models and algorithms. While stereoscopic data has been studied for long, it is only recently that feature-length stereoscopic ("3D") movies became widely available. In this thesis, we study how we can exploit the additional information provided by 3D movies for person analysis. We first explore how to extract a notion of depth from stereo movies in the form of disparity maps. We then evaluate how person detection and human pose estimation methods perform on such data. Leveraging the relative ease of the person detection task in 3D movies, we develop a method to automatically harvest examples of persons in 3D movies and train a person detector for standard color movies. We then focus on the task of segmenting multiple people in videos. We first propose a method to segment multiple people in 3D videos by combining cues derived from pose estimates with ones derived from disparity maps. We formulate the segmentation problem as a multi-label Conditional Random Field problem, and our method integrates an occlusion model to produce a layered, multi-instance segmentation. After showing the effectiveness of this approach as well as its limitations, we propose a second model which only relies on tracks of person detections and not on pose estimates. We formulate our problem as a convex optimization one, with the minimization of a quadratic cost under linear equality or inequality constraints. These constraints weakly encode the localization information provided by person detections. This method does not explicitly require pose estimates or disparity maps but can integrate these additional cues. Our method can also be used for segmenting instances of other object classes from videos. We evaluate all these aspects and demonstrate the superior performance of this new method.

The purpose of this thesis is to indemnity for damage to the family house in Studenec caused damage to water distribution The main focus of my work is to value a property by the cost method, as well as documenting damages and determining the appropriate cost of the required repairs or reconstruction in accordance with the insurance contract. Furthermore, I willpreoccupied a new insurance value of the property. In the theoretical section, fundamentalconcepts are outlined, in accordance with applicable laws and regulations

« La représentation et l’assistance du plaideur en justice » constitue un sujet classique, mais plus que jamais contemporain. Face à la crise de la justice civile, mais aussi devant son évolution rapide, les choix de politique législative actuels font preuve d’une volonté de renforcer la représentation obligatoire par avocat. Bien que la représentation et l’assistance du plaideur en justice soient utilisées quotidiennement, leur définition et leur finalité en procédure civile restent obscures. Qu’est-ce que « la représentation et l’assistance du plaideur en justice » ? À quoi sert « la représentation et l’assistance du plaideur en justice » ? Notre étude tend à la résolution de ce double problème. À cette fin, nous examinons la nature et la fonction de la représentation et de l’assistance du plaideur en justice. Quant à leur nature, il convient d’analyser leurs composantes conventionnelle et institutionnelle comportant leurs réalités intérieures et extérieures qui les définissent en droit. Quant à leur fonction, il faut approfondir leurs finalités d’intérêt privé et d’intérêt général visant respectivement la protection des droits fondamentaux du plaideur et la bonne administration de la justice. Cette étude permet d’apporter une définition de la représentation et de l’assistance du plaideur en justice, de leur restituer toute leur valeur en procédure civile au regard de leur finalité, de fournir des réponses aux problématiques rencontrées dans la pratique juridictionnelle et d’enrichir la réflexion sur l’avenir de la procédure civile. Elle aboutit à des propositions sur une réforme de la procédure civile fondée sur la représentation à l’instance par avocat. / "Legal representation and legal assistance of litigant" is a classic topic, more than ever contemporary, though. In front of civil justice crisis and its rapid evolution, current legislative choices show a willingness to strenghten legal representation by lawyer. Despite the use of legal representation and legal assistance of litigant on a daily basis, their definition and finality remain obscure. What is "legal representation and legal assistance of litigant" ? Which is the purpose of "legal representation and legal assistance of litigant" ? This study tends to solve this double question by examining the nature and the function of legal representation and legal assistance of litigant. As for their nature, it is their conventional and institutional components including their internal and external realities that contibute to their legal definition, that must be analysed. As for their function, it is necessary to delve into their private and general interest aims that respectively tend to protect the fundamental rights of the litigant and the proper administration of justice. This study permits a definition of legal representation and legal assistance of litigant, restores their value in civil procedure with regard to their purpose, provides answers to the judicial practice problems and permits to enrich the reflection on civil procedure’s futur. It leads to proposals for a reform of the civil procedure based on legal representation by lawyer.

Graphical rendering has use cases in many fields. When rendering in real time, such as in simulations or games, the time to compute each frame is of high importance. An important factor to reducing frame time is decreasing the amount of calls between the processor and graphics card. This is especially important when rendering a large amount of meshes, which is a collection of vertices representing some geometry. Two ways of achieving this are Batch and Instance rendering. This thesis aims to analyze and provide valuable insight into the factors that influence the decision between the techniques for static geometry, which is geometry that does not move. More specifically the thesis will investigate how vertex and mesh count affects the frame time. Both techniques were implemented using C++ and OpenGL and then compared against each other. The results showed that for low vertex amounts Batch rendering has lower frame time. Subsequently, at higher vertex amounts Instance rendering has lower frame time. The exact cut off depends on hardware, but in general the conclusion was that Batch rendering is better for simpler meshes while Instance rendering is better for more complex meshes. / Grafisk rendering är användbart inom många områden. När rendering sker i realtid, som i simulationer eller spel, har frame time vilket är tiden det tar att beräkna varje bildruta stor betydelse. En viktig faktor för att minska frame time är att minska antalet anrop mellan processorn och grafikkortet. Detta är särskilt viktigt vid rendering av en stor mängd meshes, vilket är en samling av noder som representerar geometri. Två sätt att uppnå detta är Batch och Instance rendering. Denna avhandling syftar till att analysera och ge värdefulla insikter i de faktorer som påverkar beslutet mellan teknikerna för statisk geometri, vilket är geometri som inte rör sig. Mer specifikt kommer avhandlingen att undersöka hur antalet noder och meshes påverkar frame time. Båda teknikerna implementerades med hjälp av C++ och OpenGL och jämfördes sedan med varandra. Resultaten visade att för låga antal noder har Batch-rendering kortare frame time. Däremot, vid högre antal noder har Instance rendering kortare frame time. Den exakta gränsen beror på hårdvaran, men den generella slutsatsen var att Batch-rendering är bättre för enklare meshes medan Instance rendering är bättre för mer komplexa meshes.