Made available in DSpace on 2014-06-11T19:26:39Z (GMT). No. of bitstreams: 0 Previous issue date: 2003-09-26Bitstream added on 2014-06-13T20:28:15Z : No. of bitstreams: 1 santos_pv_me_assis.pdf: 683228 bytes, checksum: a1b11b554219e8c3ebbb9a4f2c9ad14e (MD5) / Osíris foi um dos deuses mais importantes dentro do panteão da civilização egípcia. Encontramos alusões ao seu mito desde o começo da era dinástica até o período greco-romano, onde temos a síntese realizada por Plutarco (45-120 d.C.) no seu tratado sobre Ísis e Osíris. Através da análise desse mito, tal como narrado por Plutarco, pode-se perceber que sua influência foi muito profunda e marcante na história do Egito abrangendo questões referentes aos aspectos principais dessa sociedade. Seu mito respondia questões e anseios pertinentes a todos os egípcios sendo dessa forma adorado em todo o país. Possuía características e funções como deus relacionado aos ciclos da natureza, como a Lua, o Nilo e o grão, como mantenedor da ordem e da sucessão real e fundamentalmente como aquele que transcendeu a morte e foi reinar no Ultra-Tumba, tornando-se rei e juiz desse mundo. Portanto, nosso objetivo será mostrar que o mito de Osíris estava relacionado com todos os aspectos da vida egípcia, da paz à guerra, da seca à enchente, da peste à abundância, da posição divina do faraó à dureza da servidão e fundamentalmente, da vida à morte. Conseguindo, assim, abarcar em sua personalidade divina todos os atributos necessários para solucionar e satisfazer as necessidades de todos os estratos sociais, do rei ao servo. / Osiris was one of the most important divinities inside the panteon of Egyptian civilization. We find hints of this myth since the beginning of the Dynastyc era until the Greco-Roman period, in which we have the syntesis made by Plutarch (45-120 A.D.) in his work about Isis and Osiris. Analyzing the myth of Osiris, as it is narrated by Plutarch, we can realize that its influence was very deep and very important in the history of Egypt, reaching questions concerning the main features of this society. The myth of Osiris answered questions and wishes which were pertinent to all egyptians, so that it was adored in entire country. It possessed characteristics and functions as god related to the cycles of nature, like the Moon, the Nile River and the seed; as keeper of order and of regal succession and, fundamentally, as the one which transcended the death and went to reign in Over-Grave, becoming king and judge of that world. Thus, our purpose will be to show that the myth of Osiris was related to all features of Egyptian life, from peace to war, from dryness to inundation, from plague to plenty, from the divine position of the king to the hardness of servitude, and fundamentally, from life to death. So, the myth of Osiris got to embrace, in its divine personality, all the necessary attributes to resolve and to satisfy the needs of all social classes, from the king to the serf.

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Reserves estimation in an unconventional-reservoir setting is a daunting task because of geologic uncertainty and complex flow patterns evolving in a long-stimulated horizontal well, among other variables. To tackle this complex problem, we present a reserves-evaluation workflow that couples the traditional decline-curve analysis with a probabilistic forecasting frame. The stretched-exponential production decline model (SEPD) underpins the production behavior. Our recovery appraisal workflow has two different applications: forecasting probabilistic future performance of wells that have production history; and forecasting production from new wells without production data. For the new field case, numerical model runs are made in accord with the statistical design of experiments for a range of design variables pertinent to the field of interest. In contrast, for the producing wells the early-time data often need adjustments owing to restimulation, installation of artificial-lift, etc. to focus on the decline trend. Thereafter, production data of either new or existing wells are grouped in accord with initial rates to obtain common SEPD parameters for similar wells. After determining the distribution of model parameters using well grouping, the methodology establishes a probabilistic forecast for individual wells. We present a probabilistic performance forecasting methodology in unconventional reservoirs for wells with and without production history. Unlike other probabilistic forecasting tools, grouping wells with similar production character allows estimation of self-consistent SEPD parameters and alleviates the burden of having to define uncertainties associated with reservoir and well-completion parameters.

La présente thèse a pour objectif principal de développer des approches déterministes et heuristiques pour résoudre certaines classes de problèmes d'optimisation en Finance, Affectation et Recherche d'Informations. Il s'agit des problèmes d'optimisation non convexe de grande dimension. Nos approches sont basées sur la programmation DC&DCA et la méthode Cross-Entropy (CE). Grâce aux techniques de formulation/reformulation, nous avons donné la formulation DC des problèmes considérés afin d'obtenir leurs solutions en utilisant DCA. En outre, selon la structure des ensembles réalisables de problèmes considérés, nous avons conçu des familles appropriées de distributions pour que la méthode Cross-Entropy puisse être appliquée efficacement. Toutes ces méthodes proposées ont été mises en œuvre avec MATLAB, C/C++ pour confirmer les aspects pratiques et enrichir notre activité de recherche.

Cette thèse a pour but de développer des approches déterministes et heuristiques pour résoudre certaines classes des problèmes d'optimisation en télécommunication et la mobilité d'un réseau de transport : problèmes de routage, problèmes de covoiturage, problèmes de contrôle de l'alimentation dans un réseau sans fil, problèmes d'équilibrage du spectre dans les réseaux DSL. Il s'agit des problèmes d'optimisation non convexe de très grande taille. Nos approches sont basées sur la programmation DC&DCA, méthode de décomposition proximale et la méthode d'étiquetage des graphes. Grâce aux techniques de formulation/reformulation et de pénalité exacte, nous avons établi des programmes DC équivalents en vue de leur résolution par DCA. Selon la structure de ces problèmes, on peut fournir des décompositions DC appropriées ou de bons points initiaux de DCA. Nos méthodes ont été programmées sous MATLAB, C/C++. Ils montrent la performance de nos algorithmes par rapport à des méthodes existantes.

L’objectif de cette thèse porte sur des recherches théoriques et algorithmiques d’optimisation locale et globale via les techniques de programmation DC & DCA, Séparation et Evaluation (SE) ainsi que les techniques de relaxation DC/SDP, pour résoudre plusieurs types de problèmes d’optimisation non convexe (notamment en Optimisation Combinatoire et Optimisation Polynomiale). La thèse comporte quatre parties :La première partie présente les outils fondamentaux et les techniques essentielles en programmation DC & l’Algorithme DC (DCA), ainsi que les techniques de relaxation SDP, et les méthodes de séparation et évaluation (SE).Dans la deuxième partie, nous nous intéressons à la résolution de problèmes de programmation quadratique et linéaire mixte en variables entières. Nous proposons de nouvelles approches locales et globales basées sur DCA, SE et SDP. L’implémentation de logiciel et des simulations numériques sont aussi étudiées.La troisième partie explore des approches de la programmation DC & DCA en les combinant aux techniques SE et SDP pour la résolution locale et globale de programmes polynomiaux. Le programme polynomial avec des fonctions polynomiales homogènes et son application à la gestion de portefeuille avec moments d’ordre supérieur en optimisation financière ont été discutés de manière approfondie dans cette partie.Enfin, nous étudions dans la dernière partie un programme d’optimisation sous contraintes de type matrices semi-définies via nos approches de la programmation DC. Nous nous consacrons à la résolution du problème de réalisabilité des contraintes BMI et QMI en contrôle optimal.L’ensemble de ces travaux a été implémenté avec MATLAB, C/C++ ... nous permettant de confirmer l’utilisation pratique et d’enrichir nos travaux de recherche. / The main objective of this thesis focuses on theoretical and algorithmic researches of local and global optimization techniques to DC programming & DCA with Branch and Bound (B&B) and the DC/SDP relaxation techniques to solve several types of non-convex optimization problems (including Combinatorial Optimization and Polynomial Optimization). This thesis is divided into four parts :We present in the first part some fondamental theorems and essential techniques in DC programming & DC Algorithm (DCA), the SDP Relaxation techniques, as well as the Branch and Bound methods (B&B).In the second part, we are interested in solving mixed integer quadratic and linear programs. We propose new local and global approaches based on DCA, B&B and SDP. The implementation of software and numerical simulations have also been investigated.The third part explores the DC programming approaches & DCA combined with a B&B technique and SDP for locally and globally solving a class of polynomial programming. The polynomial program with homogeneous polynomial functionsand its application to portfolio selection problem involving higher order moments in financial optimization have been deeply studied in this part.Finally, in the last part, we present our research on optimization problems under constraints of semi-definite matrices via our DC programming approaches. This part is dedicated to the resolution of the BMI and QMI feasibility problems in the field of optimal control.All these proposed methods have been implemented with MATLAB, C++ etc., that allowing us to confirm the practical use and enrich our research works.

Cette thèse a pour but de développer des approches déterministes et heuristiques pour résoudre certaines classes des problèmes d'optimisation en télécommunication et la mobilité d'un réseau de transport : problèmes de routage, problèmes de covoiturage, problèmes de contrôle de l'alimentation dans un réseau sans fil, problèmes d'équilibrage du spectre dans les réseaux DSL. Il s'agit des problèmes d'optimisation non convexe de très grande taille. Nos approches sont basées sur la programmation DC&DCA, méthode de décomposition proximale et la méthode d'étiquetage des graphes. Grâce aux techniques de formulation/reformulation et de pénalité exacte, nous avons établi des programmes DC équivalents en vue de leur résolution par DCA. Selon la structure de ces problèmes, on peut fournir des décompositions DC appropriées ou de bons points initiaux de DCA. Nos méthodes ont été programmées sous MATLAB, C/C++. Ils montrent la performance de nos algorithmes par rapport à des méthodes existantes. / In this thesis, we focus on developing deterministic and heuristic approaches for solving some classes of optimization problems in Telecommunication and Mobility & Transport domain: Routing problems, Car pooloing problems, Power control problems in wireless network, Optimal spectrum balancing problems in DSL networks. They are large-scale nonconvex optimization problems. Our methodologies are focus on DC programming and DCA, Proximal decomposition method and Labeling method in graph theory. They are well-known as powerful tools in optimization. The considered problems were reformulated using the DC formulation/reformulation and exact penalty techniques and the DCA was used to obtain the solution. Also, depending on the structure of considered problems, we can provide appropriate DE decompositions or good initial points for DCA. All these proposed methods have been implemented with MATLAB, C/C++ to confirm the practical aspects and enhance our research works.

Basés sur les outils théoriques et algorithmiques de la programmation DC et DCA, les travaux de recherche dans cette thèse portent sur les approches locales et globales pour l'optimisation non convexe et l'optimisation globale en variables mixtes entières. La thèse comporte 5 chapitres. Le premier chapitre présente les fondements de la programmation DC et DCA, et techniques de Séparation et Evaluation (B&B) (utilisant la technique de relaxation DC pour le calcul des bornes inférieures de la valeur optimale) pour l'optimisation globale. Y figure aussi des résultats concernant la pénalisation exacte pour la programmation en variables mixtes entières. Le deuxième chapitre est consacré au développement d'une méthode DCA pour la résolution d'une classe NP-difficile des programmes non convexes non linéaires en variables mixtes entières. Ces problèmes d'optimisation non convexe sont tout d'abord reformulées comme des programmes DC via les techniques de pénalisation en programmation DC de manière que les programmes DC résultants soient efficacement résolus par DCA et B&B bien adaptés. Comme première application en optimisation financière, nous avons modélisé le problème de gestion de portefeuille sous le coût de transaction concave et appliqué DCA et B&B à sa résolution. Dans le chapitre suivant nous étudions la modélisation du problème de minimisation du coût de transaction non convexe discontinu en gestion de portefeuille sous deux formes : la première est un programme DC obtenu en approximant la fonction objectif du problème original par une fonction DC polyèdrale et la deuxième est un programme DC mixte 0-1 équivalent. Et nous présentons DCA, B&B, et l'algorithme combiné DCA-B&B pour leur résolution. Le chapitre 4 étudie la résolution exacte du problème multi-objectif en variables mixtes binaires et présente deux applications concrètes de la méthode proposée. Nous nous intéressons dans le dernier chapitre à ces deux problématiques challenging : le problème de moindres carrés linéaires en variables entières bornées et celui de factorisation en matrices non négatives (Nonnegative Matrix Factorization (NMF)). La méthode NMF est particulièrement importante de par ses nombreuses et diverses applications tandis que les applications importantes du premier se trouvent en télécommunication. Les simulations numériques montrent la robustesse, rapidité (donc scalabilité), performance et la globalité de DCA par rapport aux méthodes existantes. / Based on theoretical and algorithmic tools of DC programming and DCA, the research in this thesis focus on the local and global approaches for non convex optimization and global mixed integer optimization. The thesis consists of 5 chapters. The first chapter presents fundamentals of DC programming and DCA, and techniques of Branch and Bound method (B&B) for global optimization (using the DC relaxation technique for calculating lower bounds of the optimal value). It shall include results concerning the exact penalty technique in mixed integer programming. The second chapter is devoted of a DCA method for solving a class of NP-hard nonconvex nonlinear mixed integer programs. These nonconvex problems are firstly reformulated as DC programs via penalty techniques in DC programming so that the resulting DC programs are effectively solved by DCA and B&B well adapted. As a first application in financial optimization, we modeled the problem pf portfolio selection under concave transaction costs and applied DCA and B&B to its solutions. In the next chapter we study the modeling of the problem of minimization of nonconvex discontinuous transaction costs in portfolio selection in two forms: the first is a DC program obtained by approximating the objective function of the original problem by a DC polyhedral function and the second is an equivalent mixed 0-1 DC program. And we present DCA, B&B algorithm, and a combined DCA-B&B algorithm for their solutions. Chapter 4 studied the exact solution for the multi-objective mixed zero-one linear programming problem and presents two practical applications of proposed method. We are interested int the last chapter two challenging problems: the linear integer least squares problem and the Nonnegative Mattrix Factorization problem (NMF). The NMF method is particularly important because of its many various applications of the first are in telecommunications. The numerical simulations show the robustness, speed (thus scalability), performance, and the globality of DCA in comparison to existent methods.

Background: The increasing consumption of dietary supplements (DS) has drawn the attention of regulatory agencies, researchers and healthcare professionals. The US Food and Drug Administration (FDA) does not require premarketing assessment of DS considering them safe unless proven otherwise. However, the reporting rate of DS adverse events (DS-AE) is low. Objective: To describe pharmacists’ attitudes and knowledge of DS and DS information resources, and to determine the importance of selected attributes in pharmacists’ decisions to report a DS-AE. Methods: A convenience sample of practicing pharmacists in Virginia was surveyed using a web-based self-administered questionnaire. A conjoint analysis exercise was developed using several scenarios based on a set of five attributes: patient’s age, initiation of DS, last modification in drug therapy, evidence supporting the AE, and outcome of the AE. Participants were asked to indicate their decision to report the AE in each scenario to prescriber, drug manufacturer, DS manufacturer and FDA on a 6-point ordered scale. Participants’ attitude, knowledge of DS, demographic information, and DS information resources were also requested. Linear regression models were used to determine the relative importance of the profile attributes on a pharmacist’s decision to report the AE. The effects of other characteristics on the importance of the attributes were assessed. Results: Participants’ overall attitudes were relatively positive for the clinical use of DS but negative for safe of DS. Formal training on DS was associated with better knowledge of DS regulation. The average knowledge score of DS identification was relatively good but was low for DS regulation. Lexi-Comp® was the most widely used and available information resource and the Natural Medicines Comprehensive Database was the most useful once. The most important attribute that a pharmacist considered in the decision to report a DS-AE to DS manufacturer, drug manufacturer and FDA was the outcome of the AE followed by the evidence supporting the AE. Ranking of these two factors was the reversed in reporting to prescriber. Conclusions: Outcome and evidence of the AE are the most important factors participants considered when reporting. Other characteristics do not have an impact on the relative importance of the attributes.