Der kontinuierliche Entwicklungsprozess der modernen Informations- und Kommunikationstechnologie (IKT) bietet in rascher Folge immer wieder neue Handlungsalternativen für die Unternehmen. Als ein Resultat dieser Entwicklung ist der inzwischen hohe Grad der Globalisierung der Wirtschaft zu interpretieren. Derartige Veränderungen der wirtschaftlichen Rahmenbedingungen zwingen insbesondere kleine und mittlere Unternehmen (KMU) zu Überlegungen, wie mit dieser Entwicklung mitgehalten werden kann. Durch die i.d.R. sehr begrenzten finanziellen Möglichkeiten, einer tendenziell schlechteren Infrastruktur sowie die Beschränkung auf nur wenige Kernkompetenzen haben viele KMU Schwierigkeiten, mit den großen Konzernen zu konkurrieren. Aus diesem Grund gilt es, dass KMU auf ihre spezifischen Stärken wie schnelle Reaktionsfähigkeit und schlanke Organisationsstruktur setzen. Daher entscheiden sich zahlreiche KMU für eine Teilnahme in Netzwerken. Das Ziel derartiger unternehmensübergreifender Wertschöpfungsverbünde besteht in der Herstellung weltweit konkurrenzfähiger Produkte durch intensive kompetenzorientierte Kooperation. Dieser Ansatz wurde in der Realität bereits in zahlreichen Fällen verwirklicht. Neben dieser praxisorientierten Sicht stellen Netzwerke (und insbesondere Produktionsnetzwerke) auch ein interessantes und vielschichtiges Forschungsgebiet dar. Diesbezügliche Arbeiten konzentrieren sich entweder auf einzelne Teilbereiche wie zum Beispiel Organisation, Recht, Technik, Logistik oder Controlling oder aber stellen eine umfassende generelle Konzeption in den Mittelpunkt der Betrachtungen. Vorliegender Beitrag stellt einführend für ein theoretisch fundiertes Basiskonzept das Modell des „Hierarchielosen Regionalen Produktionsnetzes“ sowie das dafür entwickelte Betreiberkonzept „Extended Value Chain Management“ (EVCM) vor. Auf der Basis dieses Ansatzes erfolgt die konzeptionelle Beschreibung eines geeigneten Gewinnverteilungsmodells unter Berücksichtigung von Anreiz- und Sanktionsmechanismen für die Netzwerkteilnehmer. Als Hauptziel wird in diesem Zusammenhang die Maximierung des Nutzens für das gesamte Produktionsnetz formuliert.

The subject of this thesis is the maximization of the information divergence from an exponential family on a finite set, a problem first formulated by Nihat Ay. A special case is the maximization of the mutual information or the multiinformation between different parts of a composite system. My thesis contributes mainly to the mathematical aspects of the optimization problem. A reformulation is found that relates the maximization of the information divergence with the maximization of an entropic quantity, defined on the normal space of the exponential family. This reformulation simplifies calculations in concrete cases and gives theoretical insight about the general problem. A second emphasis of the thesis is on examples that demonstrate how the theoretical results can be applied in particular cases. Third, my thesis contain first results on the characterization of exponential families with a small maximum value of the information divergence.:1. Introduction 2. Exponential families 2.1. Exponential families, the convex support and the moment map 2.2. The closure of an exponential family 2.3. Algebraic exponential families 2.4. Hierarchical models 3. Maximizing the information divergence from an exponential family 3.1. The directional derivatives of D(*|E ) 3.2. Projection points and kernel distributions 3.3. The function DE 3.4. The first order optimality conditions of DE 3.5. The relation between D(*|E) and DE 3.6. Computing the critical points 3.7. Computing the projection points 4. Examples 4.1. Low-dimensional exponential families 4.1.1. Zero-dimensional exponential families 4.1.2. One-dimensional exponential families 4.1.3. One-dimensional exponential families on four states 4.1.4. Other low-dimensional exponential families 4.2. Partition models 4.3. Exponential families with max D(*|E ) = log(2) 4.4. Binary i.i.d. models and binomial models 5. Applications and Outlook 5.1. Principles of learning, complexity measures and constraints 5.2. Optimally approximating exponential families 5.3. Asymptotic behaviour of the empirical information divergence A. Polytopes and oriented matroids A.1. Polytopes A.2. Oriented matroids Bibliography Index Glossary of notations

Hidden Markov Models (HMMs) have seen widespread use in a variety of applications ranging from speech recognition to gene prediction. While developed over forty years ago, they remain a standard tool for sequential data analysis. More recently, Latent Dirichlet Allocation (LDA) was developed and soon gained widespread popularity as a powerful topic analysis tool for text corpora. We thoroughly develop LDA and a generalization of HMMs and demonstrate the conjunctive use of both methods in predictive data analysis for health care problems. While these two tools (LDA and HMM) have been used in conjunction previously, we use LDA in a new way to reduce the dimensionality involved in the training of HMMs. With both LDA and our extension of HMM, we train classifiers to predict development of Chronic Kidney Disease (CKD) in the near future.

Yes / This article proposes a novel technique for operation of distribution networks with considering active network management (ANM) schemes and demand response (DR) within a joint active and reactive distribution market environment. The objective of the proposed model is to maximize social welfare using market-based joint active and reactive optimal power flow. First, the intermittent behavior of renewable sources (solar irradiance, wind speed) and load demands is modeled through scenario-tree technique. Then, a network frame is recast using mixed-integer linear programming, which is solvable using efficient off-the-shelf branch-and cut solvers. Additionaly, this article explores the impact of wind and solar power penetration on the active and reactive distribution locational prices within the distribution market environment with integration of ANM schemes and DR. A realistic case study (16-bus UK generic medium voltage distribution system) is used to demonstrate the effectiveness of the proposed method. / This work was supported in part by the Ministry of Higher Education Scientific Research in Iraq and in part by British Academy under Grant GCRFNGR3\1541.

[pt] Richard Posner, adepto do critério analítico econômico do direito, parametrizou o desenvolvimento de sua Teoria do Direito na construção das decisões judiciais, elaborando, para tanto, um estudo eivado de elementos interdisciplinares descritos nas ciências jurídica e da economia, buscando, com isso, apresentar um cenário estável e seguro para aplicação do direito. Desta forma, a presente dissertação apresentará, em seu primeiro capítulo os elementos fundamentais das ciências econômicas, em especial seu conceito de eficiência, cujo escopo será essencial para o desenvolvimento do trabalho de Richard Posner. Já em seu segundo capítulo, o trabalho voltará seu olhar para o desenvolvimento e desdobramento do pensamento do autor americano, demonstrando o início de seu processo investigativo até seu giro pragmático, provocado, sobretudo, pelas intervenções e críticas de Ronald Dworkin, chegando, por fim, ao terceiro capítulo no qual o objeto de investigação será o processo de metrificação do pensamento jurídico, demonstrando a teoria da maximização da riqueza desenvolvida por Posner e evidenciando as razões pelas quais o autor renegou o trabalho de Pareto e de Kaldor-Hicks. Em sua conclusão, esta dissertação demonstrará o processo evolutivo do pensamento de Richard Posner, em especial o processo de metrificação da eficiência baseada na maximização da riqueza, que embasará o processo decisório dos Juízes e promoverá, segundo sua visão, a construção da Teoria do Direito. / [en] Richard Posner, adept of the economic analytical criterion of law, parameterized the development of his Theory of Law in the construction of judicial decisions, developing, for that purpose, a study full of interdisciplinary elements described in the legal and economic sciences, seeking, with this, describe a stable and safe scenario for the application of the law. In this way, the present dissertation will present, in its first chapter, the fundamental elements of economic sciences, especially its concept of efficiency, whose scope will be essential for the development of Richard Posner s work, in the second chapter the work will turn its gaze to the development and unfolding of the American author s thought, demonstrating the beginning of his investigative process until its pragmatic turn, provoked, above all, by Ronald Dworkin s interventions and criticisms, reaching, finally, the third chapter where the object of investigation will be the process of metrification of legal thought, demonstrating the theory of maximization of wealth developed by Posner and evidencing the reasons why the author disowned the work of Pareto and Kaldor-Hicks. In its conclusion, this dissertation will demonstrate the evolutionary process of Richard Posner s thought, in particular the process of metrification of efficiency based on the maximization of wealth, which will base the decision-making process of the Judges and will promote, according to his vision, the construction of the Theory of Law.

Distributed generators (DGs) are proposed as a possible solution to supply economic and reliable electricity to customers. It is adapted to overcome the challenges that are characterized by centralized generation such as transmission and distribution losses, high cost of fossil fuels and environmental damage. This work presents the basic principles of integrating renewable DGs in low voltage distribution networks and particularly focuses on the operation of DG installations and their impacts on active and reactive power. In this thesis, a novel technique that applies the stochastic approach for the operation of distribution networks with considering active network management (ANM) schemes and demand response (DR) within a joint active and reactive distribution market environment is proposed. The projected model is maximized based on social welfare (SW) using market-based joint active and reactive optimal power flow (OPF). The intermittent behaviour of renewable sources (such as solar irradiance and wind speed) and the load demands are modelled through Scenario-Tree technique. The distributed network frame is recast using mixed-integer linear programming (MILP) that is solved by using the GAMS software and then the obtained results are being analysed and discussed. In addition, the impact of wind and solar power penetration on the active and reactive distribution locational prices (D-LMPs) within the distribution market environment is explored in terms of the maximization of SW considering the uncertainty related to solar irradiance, wind speed and load demands. Finally, a realistic case study (16-bus UK generic medium voltage distribution system) is used to demonstrate the effectiveness of the proposed method. Results show that ANM schemes and DR integration lead to an increase in the social welfare and total dispatched active and reactive power and consequently decrease in active and reactive D-LMPs. / Ministry of Higher Education and Scientific Research - Iraq / The selected author's publications, the published versions of which were attached at the end of the thesis, have been removed due to copyright.

Pendant la pandémie de Covid-19, les minorités raciales et les groupes économiquement défavorisés ont connu des taux accrus d’infection, d’hospitalisation et de décès dans les zones urbaines. Cette disparité témoigne de l’oppression systématique à laquelle sont confrontées les minorités raciales et la classe ouvrière, qui s’étend évidemment aux services de santé. Les inégalités flagrantes en matière de santé étaient évidentes avant que les vaccins ne soient disponibles, nous ne pouvons donc pas simplement les attribuer à des attitudes culturelles d’hésitation à la vaccination. Dans ce travail, nous présentons des solutions pour optimiser la distribution équitable des vaccins pour différents groupes démographiques, afin de promouvoir un accès équitable aux vaccins lors du premier cycle d’attribution. Nous nous appuyons sur des travaux antérieurs pour construire des réseaux de mobilité de trois zones métropolitaines américaines en utilisant des données de visites réelles dans des lieux publics au cours des premières semaines de la pandémie. Nous proposons une nouvelle méthode utilisant la maximisation de l’influence pour détecter les quartiers les plus influents de la zone urbaine en termes d’efficacité dans la propagation de la maladie. Nous modélisons ensuite la propagation ultérieure de la maladie avec ces quartiers sélectionnés vaccinés. De plus, nous introduisons des considérations d’équité afin de mettre en œuvre un accès équitable aux vaccins pour les groupes raciaux et les groupes de revenus du réseau. Pour fusionner nos solutions avec les stratégies actuelles, nous combinons nos stratégies équitables avec une méthode de priorisation pour les groupes plus âgés du réseau. / During the Covid-19 pandemic, racial minorities and economically-disadvantaged groups experienced heightened rates of infection, hospitalization and death in urban areas. This disparity speaks to the systematic oppression faced by racial minorities and the working classes, which evidently extends to healthcare provisions. The stark inequalities in health outcomes were clear before vaccines became available, so we cannot simply attribute this to cultural attitudes of vaccine hesitancy. In this work, we present solutions to optimize the fair distribution of vaccines for different demographic groups, in order to promote equitable vaccine access in the first round of allocation. We build on previous work to construct mobility networks of three US metropolitan areas using data of real visits to public places during the first weeks of the pandemic. We propose a novel method using influence maximization (IM) to detect the most influential neighborhoods in the urban area in terms of efficacy in spreading the disease. We then model the subsequent disease spread with these selected neighborhoods vaccinated. Additionally, we introduce fairness considerations, to implement equitable vaccine access for racial groups and income groups in the network. To merge our solutions with current strategies, we combine our fair strategies with a prioritization method for older-age groups in the network.

Pharmacogivilance consists in carefully monitoring drugs in order to re-evaluate their risk for people’s health. The sooner the Adverse Drug Reactions are detected, the sooner one can act consequently. This thesis aims at discovering such reactions in electronical health records under the constraint of lacking annotated data, in order to replicate the scenario of the Regional Center for Pharmacovigilance of Nice. We investigate how in a semi-supervised learning design the unlabeled data can contribute to improve classification scores. Results suggest an excellent recall in discovering adverse reactions and possible classification improvements under specific data distribution. / Läkemedelsövervakningen består i kolla försiktigt läkemedlen så att utvärdera dem för samhällets hälsa. Ju tidigare de läkemedelsrelaterade biverkningarna upptäcks, desto tidigare man får handla dem. Detta exjobb söker att upptäcka de där läkemedelsrelaterade biverkningarnna inom elektroniska hälsopost med få datamärkningar, för att återskapa Nice regionalt läkemedelelsöveraknings-centrumets situationen. Vi undersöker hur en halvväglett lärande lösning kan hjälpa att förbättra klassificeringsresultat. Resultaten visar en god återställning med biverknings-upptäckning och möjliga förbättringar.

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