This thesis deals with the stochastic optimization problem of hydro reservoir manage- ment. External inflows and market electricity price are both considered as random inputs to the model, which is designed as joint chance constrained programming. The main goal of the optimization problem is to maximize the profit from hydro energy usage together with minimizing the cost of used water. The random component is modelled by suitable stochastic processes based on historical data and then approximated via scenarios. Sea- sonal deterministic model is another model that is presented in this thesis. This model helps appraise water stored in every each reservoir's compartment. The estimates of water values are based on dual variables. Finally, in the practical part the hydro reservoir ma- nagement problem is applied to the real hydro valley located on the Vltava river. This part also deals with an option of increasing the number of pumping stations in this particular hydro valley.

Le développement majeur de la thèse a été consacré au problème d’optimisation du choix de dose dans les essais de recherche de dose, en phase II. Nous avons considéré ce problème sous l’angle des fonctions d’utilité. Nous avons alloué une valeur d’utilité aux doses, le problème pour le sponsor étant de trouver la meilleure dose, c’est-à-dire celle dont l’utilité est la plus élevée.Dans ce travail, nous nous sommes limités à une seule fonction d’utilité, intégrant deux composantes: une composante liée à l’efficacité (la POS=puissance d’un essai de phase III de 1000 patients de cette dose contre placebo) et une autre liée à la safety. Pour cette dernière, nous avons choisi de la caractériser par la probabilité prédictive d’observer un taux de toxicité inférieur ou égal à un certain seuil (que nous avons fixé à 0.15) en phase III (toujours pour un essai de 1000 patients au total). Cette approche a l’avantage d’être similaire aux concepts utilisés dans les essais de phase I en oncologie qui ont notamment pour objectif la recherche de la dose liée à une toxicité limite (notion de ”Dose limiting Toxicity”).Nous avons retenu une approche bayésienne pour l’analyse des données de la phase II.Mis à part les avantages théoriques connus de l’approche bayésienne par rapport à l’approche fréquentiste (respect du principe de vraisemblance, dépendance moins grande aux résultats asymptotiques, robustesse), nous avons choisi l’approche bayésienne pour plusieurs raisons:• Combinant, par définition même de l’approche bayésienne, une information a priori avec les données disponibles, elle offre un cadre plus flexible la prise de décision du sponsor: lui permettant notamment d’intégrer de manière plus ou moins explicite les informations dont il dispose en dehors de l’essai de la phase II.• L’approche bayésienne autorise une plus grande flexibilité dans la formalisation des règles de décision.Nous avons étudié les propriétés des règles de décisions par simulation d’essais de phase II de différentes tailles: 250, 500 et 1000 patients. Pour ces deux derniers design nous avons aussi évalué l’intérêt de d’effectuer une analyse intermédiaire lorsque la moitié des patients a été enrôlée (c’est-à-dire avec respectivement les premiers 250 et 500 patients inclus). Le but était alors d’évaluer si, pour les essais de phase II de plus grande taille, s’autoriser la possibilité de choisir la dose au milieu de l’étude et de poursuivre l’étude jusqu’au bout si l’analyse intermédiaire n’est pas concluante permettait de réduire la taille de l’essai de phase II tout en préservant la pertinence du choix de dose final. / The main development of the thesis was devoted to the problem of dose choice optimization in dose-finding trials, in phase II. We have considered this problem from the perspective of utility functions. We have allocated a utility value to the doses itself, knowing that the sponsor’s problem was now to find the best dose, that is to say, the one having the highest utility. We have limited ourselves to a single utility function, integrating two components: an efficacy-related component (the PoS = the power of a phase III trial - with 1000 patients - of this dose versus placebo) and a safety-related component. For the latter, we chose to characterize it by the predictive probability of observing a toxicity rate lower or equal to a given threshold (that we set to 0.15) in phase III (still for a trial of 1000 patients in total). This approach has the advantage of being similar to the concepts used in phase I trials in Oncology, which particularly aim to find the dose related to a limiting toxicity (notion of "Dose limiting Toxicity").We have adopted a Bayesian approach for the analysis of phase II data. Apart from the known theoretical advantages of the Bayesian approach compared with the frequentist approach (respect of the likelihood principle, less dependency on asymptotic results, robustness), we chose this approach for several reasons:• It provides a more flexible framework for the decision-making of the sponsor because it offers the possibility to combine (by definition of the Bayesian approach) a priori information with the available data: in particular, it offers the possibility to integrate, more or less explicitly, the information available outside the phase II trial.• The Bayesian approach allows greater flexibility in the formalization of the decision rules.We studied the properties of decision rules by simulating phase II trials of different sizes: 250, 500 and 1000 patients. For the last two designs (500 and 1000 patients in phase II), we have also evaluated the interest of performing an interim analysis when half of the patients are enrolled (i.e. with the first 250and the first 500 patients included respectively). The purpose was then to evaluate whether or not, for larger phase II trials, allowing the possibility of choosing the dose in the middle of the study and continuing the study to the end if the interim analysis is not conclusive, could reduce the size of the phase II trial while preserving the relevance of the final dose choice.

Ce travail s'inscrit dans le cadre du projet FUI RIDER (Research for IT Driven Energy efficiency) qui vise à développer un système de gestion de l'énergie faiblement dépendant du bâtiment à contrôler et propose une nouvelle approche pour réduire les coûts énergétiques. Cette approche exploite la notion de confort thermique afin de calculer de nouvelles consignes à fournir au système de contrôle du conditionnement du bâtiment. L'approche s'appuie sur l'idée que le confort thermique est une notion multidimensionnelle subjective. La littérature propose des modèles statistiques pour appréhender le confort thermique. Malheureusement, ces modèles sont fortement non linéaires et non interprétables ce qui rend difficile leur utilisation pour la conduite ou l'optimisation. Nous proposons un nouveau modèle de confort basé sur la théorie de l'utilité multi attributs et les intégrales de Choquet. L'intérêt d'un tel modèle est qu'il est interprétable en termes de préférences pour la conduite, linéaire par simplexe ce qui facilite la résolution des problèmes d'optimisation, et plus concis qu'un système de contrôle à base de règles. Dans la seconde partie de ce travail, le THermal Process Enhancement (THPE) s'intéresse à l'obtention efficiente des consignes calculées avec le modèle du confort thermique. Le THPE se base sur un raisonnement approché établi à partir d'un modèle qualitatif enrichi EQM (Extended Qualitative Model). L'EQM est le résultat de l'étude mathématique et qualitative des équations différentielles régissant les processus thermiques. Il est enrichi en continu par un système de gestion de l'expérience basé sur un apprentissage avec pénalités qui fournit les informations quantitatives nécessaires pour inférer des recommandations de conduite quantifiées à partir des tendances modélisées dans l'EQM. L'EQM et les raisonnements associés requièrent peu de paramètres et sont opérationnels même si la base d'apprentissage est initialement vide au lancement de RIDER. Le système de gestion de l'expérience permet simplement de quantifier les recommandations et de converger plus vite vers une commande optimale. Le raisonnement à base de modèles qui supporte notre approche est faiblement dépendant du processus thermique, pertinent dès le lancement de RIDER et se prête facilement au changement d'échelle de l'analyse thermique d'un bâtiment. Les performances de notre THPE, sa stabilité et son adaptation par rapport aux variations de l'environnement sont illustrées sur différents problèmes de contrôle et d'optimisation. Les commandes optimales sont généralement obtenues en quelques itérations et permettent d'avoir un contrôle adaptatif et individuel des pièces d'un bâtiment. / The present work is part of the FUI RIDER project (Research for IT Driven Energy efficiency). It aims to develop an energy management system that has to be weakly dependent on building's specificities in order to be easily deployed in different kinds of buildings. This work proposes a new approach based on the thermal comfort concept in order to reduce energy costs. This approach takes advantage of the thermal comfort concept in order to compute new optimized setpoints for the building energy control system. It relies on the idea that thermal comfort is a subjective multidimensional concept that can be used to reduce energy consumption. The literature provides statistical thermal comfort models but their complexity and non-linearity make them not useful for the control and optimization purposes. Our new thermal comfort model is based on the multi attributes utility theory and Choquet integrals. The advantages of our model are: its interpretability in term of preference relationships, its linearity in simplex regions which simplifies optimization problems' solving, and its compact form which is more tractable than a rule based control formalism. In the second part of this work, the THermal Process Enhancement (THPE) proposes a control system approach to efficiently reach the optimized setpoints provided by the comfort model. The THPE proposes an efficient and simple thermal control approach based on imprecise knowledge of buildings' special features. Its weak data-dependency ensures the scalability and simplicity of our approach. For this, an extended thermal qualitative model (EQM) is proposed. It is based on a qualitative description of influences that actions' parameters may have on buildings' thermal performances. This description results from the mathematical and qualitative analysis of dynamical thermal behaviors. Our thermal qualitative model is then enriched by online collecting and assessing previous thermal control performances. The online learning provides the necessary quantitative information to infer quantified control recommendations from the qualitative tendencies displayed by the EQM. Thus, an approximate reasoning based on the EQM and an online learning coupled with a penalty function provides smart thermal control functionalities. The EQM based approximate reasoning guarantees our control system weak dependency with regard to the building special features as well as its multi-scale applicability and its relevancy even for RIDER's first start when the learning database lacks of information. The performances of our THPE are assessed on various types of control and optimization issues. An optimal control is generally achieved in a few iterations which allows providing an adaptive and individual control of building's rooms.

[pt] Em problemas de decisão sob incerteza que dependam da preferência entre fluxos multi-período, como é o caso dos problemas de comercialização de contratos de energia elétrica no Brasil, o agente deve saber expressar sua preferência por diferentes distribuições em cada período e, além disso, deve também especificar uma preferência entre períodos. Classicamente a abordagem utilizada é definir um funcional de preferência de von Neumann e Morgenstern separável entre os períodos, composto pela soma da esperança de utilidades que modelam a preferência em cada período. Então, para expressar a preferência entre períodos, esta soma é ponderada por um fator de desconto que visa expressar a impaciência do agente no consumo entre os períodos. Nesta abordagem, a especificação do fator de desconto torna-se uma tarefa bastante subjetiva, uma vez que estamos ponderando utilidades esperadas e não valores monetários. Devido a essa subjetividade e da dificuldade de se especificar a própria função utilidade de cada período, os grupos de finanças divergiram para uma abordagem mais pragmática, baseada na análise e controle dos riscos assumidos em suas decisões. Neste sentido, a empresa que busca maximizar a expectativa de lucro, especifica em valores monetários, um conjunto de restrições sobre as perdas que esta está disposta a incorrer, baseando-se para isso em suas probabilidades de ocorrência. Assim, durante as ultimas quatro décadas, muitas pesquisas e desenvolvimentos foram realizados nesta área, no sentido de se estabelecer medidas de risco que proporcionassem propriedades desejáveis para essa classe de problemas. Desta forma, criou-se um gap entre as duas abordagens, financeira e econômica, as quais possuem raízes em comum: modelar o comportamento de agentes frente ao risco. Assim sendo, esta tese tem três objetivos: (i) propor uma abordagem alternativa para o uso de funções utilidades em problemas de comercialização de energia elétrica multi-período, baseada no valor presente dos equivalentes certos de cada período; (ii) mostrar como tal abordagem pode ser modelada matematicamente e formulada através de um problema de programação linear inteira mista (PLIM) ao considerarmos uma função utilidade linear por partes, e (iii) mostrar a conexão entre a teoria de utilidade e problemas de maximização da renda esperada sujeito a restrições de risco do tipo alfa-CVaR. / [en] In decision under uncertainty problems that depend on multi- period preferences, as the case of trading electricity contracts in Brazil, agents should expresses their inter and intratemporal preferences. The classical economical approach is to define a time separable von Neumann and Morgenstern utility functional. This functional is composed by the sum of the expected utility of each period times an impatience factor that should express the agent`s intertemporal preference. This approach demands the specification of a subjective impatience factor, which should weight utilities units. Due to this subjectiveness and its estimation difficulties, the applied financial groups started to develop more pragmatic approaches based on risk control. In this sense, companies that maximize expected profit will impose constraints on acceptable losses using estimated occurrence probabilities of different outcomes. In this sense, the economical and applied financial approaches have been diverging in the last four decades and, during this time, many studies and developments have been done in the risk metrics field to generate and prove stability and coherence properties for the proposed metrics. This thesis has three main objectives: (i) propose an alternative approach for multi-period decisions problems based on the present value of the certainty equivalent of each period; (ii) show how this approach can be modeled as a mixed integer linear programming problem (MILP) when adopting a piecewise linear utility function; and (iii) provide connections between utility theory and expected maximization problems constrained to alpha-CVaR risk metrics.

<p>In this thesis we study algorithms and architectures that can provide a better Quality of Experience (QoE) for streaming video systems and services. With cases and examples taken from the application scenarios of football on mobile phones, we address the fundamental problems behind streaming video services. Thus, our research results can be applied and extended to other networks, to other sports and to other cultural activities.</p><p>In algorithm development, we propose five different schemes. We suggest a blind motion estimation and a trellis based motion estimation with dynamic programming algorithms for Wyner-Ziv coding. We develop a trans-media technology, vibrotactile coding of visual signals for mobile phones. We propose a new bandwidth prediction scheme for real-time video conference. We also provide an effective method based on dynamic programming to select optimal services and maximize QoE.</p><p>In architecture design, we offer three architectures for real-time interactive video and two for streaming live football information. The former three are: a structure of motion estimation in Wyner-Ziv coding for real-time video; a variable bit rate Wyner-Ziv video coding structure based on multi-view camera array; and a dynamic resource allocation structure based on 3-D object motion. The latter two are: a vibrotactile signal rendering system for live information; and a Universal Multimedia Access architecture for streaming live football video.</p><p>In QoE exploration, we give a detailed and deep discussion of QoE and the enabling techniques. We also develop a conceptual model for QoE. Moreover we place streaming video services in a framework of QoE. The new general framework of streaming video services allows for the interaction between the user, content and technology.</p><p>We demonstrate that it is possible to develop algorithms and architectures that take into account the user's perspective. Quality of Experience in video mobile services is within our reach.</p>

In this thesis we study algorithms and architectures that can provide a better Quality of Experience (QoE) for streaming video systems and services. With cases and examples taken from the application scenarios of football on mobile phones, we address the fundamental problems behind streaming video services. Thus, our research results can be applied and extended to other networks, to other sports and to other cultural activities. In algorithm development, we propose five different schemes. We suggest a blind motion estimation and a trellis based motion estimation with dynamic programming algorithms for Wyner-Ziv coding. We develop a trans-media technology, vibrotactile coding of visual signals for mobile phones. We propose a new bandwidth prediction scheme for real-time video conference. We also provide an effective method based on dynamic programming to select optimal services and maximize QoE. In architecture design, we offer three architectures for real-time interactive video and two for streaming live football information. The former three are: a structure of motion estimation in Wyner-Ziv coding for real-time video; a variable bit rate Wyner-Ziv video coding structure based on multi-view camera array; and a dynamic resource allocation structure based on 3-D object motion. The latter two are: a vibrotactile signal rendering system for live information; and a Universal Multimedia Access architecture for streaming live football video. In QoE exploration, we give a detailed and deep discussion of QoE and the enabling techniques. We also develop a conceptual model for QoE. Moreover we place streaming video services in a framework of QoE. The new general framework of streaming video services allows for the interaction between the user, content and technology. We demonstrate that it is possible to develop algorithms and architectures that take into account the user's perspective. Quality of Experience in video mobile services is within our reach.

The selection of investment strategies and managing investment funds via employing portfolio insurance methods play an important role in asset liability management. Insurance strategies are designed to limit downside risk of portfolio while allowing some participation in potential gain of upside markets. In this thesis, we provide an extensive overview and investigation, particularly on the two most prominent portfolio insurance strategies: the Constant Proportion Portfolio Insurance (CPPI) and the Option-Based Portfolio Insurance (OBPI). The aim of the thesis is to examine, analyze and compare the portfolio insurance strategies in terms of their performances at maturity, via some of their statistical and dynamical properties, and of their optimality over the maximization of expected utility criterion. This thesis presents the financial market model in continuous-time containing no arbitrage opportunies, the CPPI and OBPI strategies with definitions and properties, and the analysis of these strategies in terms of comparing their performances at maturity, of their statistical properties and of their dynamical behaviour and sensitivities to the key parameters during the investment period as well as at the terminal date, with both formulations and simulations. Therefore, we investigate and compare optimal portfolio strategies which maximize the expected utility criterion. As a contribution on the optimality results existing in the literature, an extended study is provided by proving the existence and uniqueness of the appropriate number of shares invested in the unconstrained allocation in a wider interval.

In this thesis, we analyze allocation of two separate resources in wireless networks: transmit power and buffer space. Controlled allocation of power can provide good performance for both users and the network. Although centralized mechanisms are possible, distributed power control algorithms are preferable for efficient operation of the network. Viewing distributed power allocation as the collection of rational decisions of each user, we make game theoretic problem formulations, devise distributed algorithms and analyze them. First, equilibrium analysis of a vector power control game based on network energy efficiency in a multiple access point wireless network is presented. Then, a distributed mechanism is proposed that can smooth admission control type power control so that every user can stay in the system. Introducing a new externality into utility function, a game theoretic formulation that results in desired distributed actions is made. Next, the proposed externality is investigated in a control theoretic framework. Convergence of gradient based iterative power updates are investigated and stability of corresponding continuous time dynamical system is established. In the final part of the thesis, allocation of buffer space is addressed in a wireless downlink using a queueing theoretic framework. An efficient algorithm that finds optimal buffer partitioning is proposed and applications of the algorithm for different scenarios are illustrated. Implications of the results about cross layer design and multiuser diversity are discussed.

本研究分析消費者如何在不同的社群網路間作出選擇，當用戶使用社群網站的同時，產生與朋友互相連結、分享資訊、聯絡感情等正面網路外部性，且此外部性隨著社群網站的功能越強大、隱私設定越開放而大幅增加，使用戶使用越開放的平台產生的效用越高。 但此現象同時帶給使用者相對程度的威脅：越開放的平台越無法對隱私權進行有效控制，換言之，越開放的平台越 「不願意」 對隱私權進行規範。隨著新興社群網站漸趨開放，用戶一方面享受朋友高度連結產生的正面效用，另一方面承受失去個人隱私權帶來的負面效用。且當重大侵犯隱私權事件發生，此正面外部性將如同雙面刃般轉化為傷害用戶的利器，其高度的好友連結度反而用戶間無一倖免產生強烈的效用損失。 傳統社群網路不必然會被開放性的新興社群網路所取代，因此本論文分析了純粹社群均衡、雙重均衡與社群優勢均衡的情形等多種社群網路均衡型態。 / This thesis analyzes social network asoption by consumers. The linkage with friends is nodeled as positive network effect. That is , the higher the amount of friends a user connects on a social network site, the higher the extra benefits she derives other than the direct ututility via usage. On the other hand, as new social network sites demonstrate: openness inproves connecting potential but gives way to privacy cncern.A privacy breaching event will rattle the socialty connected group to a drastic degree. Throung the interaction of both the positive and the negative network effects, we find that many types of social network equilibrium can be sustained.

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