: Este trabalho tem como objeto o redirecionamento na política externa (RPE) - conceituado como as mudanças mais radicais, abrangentes e rápidas em política externa. Para analisar este fenômeno, são buscadas as principais condições conjunturais que podem aumentar a chance de ocorrência deste evento. Estas condições estão relacionadas ao conceito de Janela Política, que representa o período em que é rompida a inércia política e os tomadores de decisões têm condições de iniciar um processo de RPE. Objetivo: encontrar e delimitar quais as condições conjunturais que aumentam as chances de ocorrência de um RPE. Método: são utilizadas ferramentas metodológicas qualitativas e quantitativas. No segundo capítulo, a análise é feita por meio de um modelo de sobrevivência (Cox Proportional Hazard Model) que analisa o efeito das variáveis sobre os riscos de ocorrência do evento em foco, definido como as alterações mais extremas de comportamento nas votações da Assembleia Geral das Nações Unidas. No terceiro capítulo, é desenvolvida uma análise qualitativa histórica focando especificamente nos casos mais radicais de RPE, buscando identificar padrões comuns no desencadeamento dos processos em estudo; com base nestes casos, são desenvolvidas tipologias explicativas para identificar diferentes caminhos causais que levam ao evento em tela. Resultados: foi identificado que mudanças de regime e de líder político, no âmbito doméstico, e intervenções militares de potências estrangeiras aumentam os riscos de ocorrência de RPE; adicionalmente, a alta polarização política e a mudança de regime, a crise política doméstica com envolvimento de atores internacionais, os processos de isolamento internacional com imposição de sanções econômicas e os períodos de crise econômica com questionamento do modelo econômico vigente por parte dos atores políticos podem combinadamente levar à ocorrência de RPE. Conclusões: apesar da importância do interesses de atores políticos em empreender um projeto de RPE, foi identificado que determinados eventos aumentam os riscos deste processo ocorrer. / This thesis object is the foreign policy restructuring (FPR) - conceptualized as the most radical, encompassing, and fast changes in foreign policy. To analyze this phenomenon, there will be sought the main conjuncture conditions that might enhance the chances of this event occurrence. These conditions are related to the Policy Window concept, that represents a period during which the political inertia is disrupted and decision makers have the circumstances to undertake a FPR process. Objective: find and outline the conjectural conditions and variables that increase the chances of occurrence of a FPR. Methods: it will be used qualitative and quantitative methodological tools. In the second chapter, a survival model (Cox Proportional Hazard Model) analyses the effect variables related to the Policy Window concept over the risks of happening a FPR, defined as the most extreme changes of behavior in United Nations General Assembly roll-call votes. In the third chapter, a historical qualitative analysis is undertaken focusing exclusively on the most radical cases of FPR to develop explanatory typologies in order to identify causal conjunctures and common patters that lead to the outcome. Results: we identified that regime and political leader changes, in the national context, and military interventions by foreign powers enhance the risks of FPR occurrence; additionally, high political polarization combined with regime change, political crisis with international forces involvement, processes of international isolation with economic sanctions enforcement, and economic crises with political actors questioning the current economic model might be combined, configuring causal paths to a FPR. Conclusion: despite the importance of main political actors interest in implementing a FPR process, we identified that specific conjunctures and events raise the risks of a positive outcome.

Different applications of communication networks have different requirements that depend on the type of application. We consider the problem of differentiating between delay-sensitive applications based on their average delay requirements, as may be of interest in signalling networks. We consider packets of different classes that are to be transmitted on the same link with different average delay requirements, to reside in separate queues with the arrival statistics for the queues being specified. This statistical multiplexer has to schedule packets from different queues in so that the average delays of the queues approach the specified target delays as quickly as possible. For simplicity, we initially consider a discrete-time model with two queues and a single work-conserving server, with independent Bernoulli packet arrivals and unit packet service times. With arrival rates specified, achieving mean queue lengths in a ratio which corresponds to the ratio of target mean delays is a means of achieving individual target mean delays. We formulate the problem in the framework of Markov decision theory. We study two scheduling policies called Queue Length Balancing and Delay Balancing respectively, and show through numerical computation that the expectation of magnitude of relative error in θ (1/m) and θ (1/√m) respectively, and that the expectation of the magnitude of relative error in weighted average delays decays as θ (1/√m) and θ (1/m) respectively, where m is the averaging interval length. We then consider the model for an arbitrary number of queues each with i.i.d. batch arrivals, and analyse the errors in the average delays of individual queues. We assume that the fifth moment of busy period is finite for this model. We show that the expectation of the absolute value of error in average queue length for at least one of the queues decays at least as slowly as θ (1/√m), and that the mean squared error in queue length for at least one of the queues decays at least as slowly as θ (1/m). We show that the expectation of the absolute value of error in approximating Little’s law for finite horizon is 0 (1/m). Hence, we show that the mean squared error in delay for at least one of the queues decays at least slowly as θ (1/m). We also show that if the variance of error in delay decays for each queue, then the expectation of the absolute value of error in delay for at least one of the queues decays at least as slowly as θ (1/√m).

Migrationsverket är en myndighet som prövar ansökningar från personer som vill söka skydd, ha medborgarskap, studera eller vill jobba i Sverige. Då det på senare tid varit en stor ökning i dessa ansökningar har tiden för vilket ett beslut tar ökat. Varje typ av ansökning (exempelvis medborgarskap) är en process som består av flera steg. Hur beslutet går igenom dessa steg kallas för flöde. Migrationsverket vill därför öka sin flödeseffektivitet. När beslutet är klart och personen tagit del av det men inte är nöjd kan denne överklaga. Detta är en av de mest komplexa processerna på Migrationsverket. Syftet är analysera hur lång tid denna process tar och vilka steg i processen som påverkar tiden. Ett steg (som senare visar sig ha en stor effekt på tiden) är yttranden. Det är när domstolen begär information om vad personen som överklagar har att säga om varför denne överklagar. För att analysera detta var två metoder relevanta, accelerated failure time (AFT) och \multi-state models (MSM). Den ena kan predicera tid till händelse (AFT) medan den andra kan analysera effekten av tidspåverkan (MSM) i stegen. Yttranden tidigt i processen har stor betydelse för hur snabbt en överklagan får en dom samtidigt som att antal yttranden ökar tiden enormt. Det finns andra faktorer som påverkar tiden men inte i så stor grad som yttranden. Då yttranden tidigt i processen samtidigt som antal yttranden har betydelse kan flödeseffektiviteten ökas med att ta tid på sig att skriva ett informativt yttrande som gör att domstolen inte behöver begära flera yttranden. / The Swedish Migration Board is an agency that review applications from individuals who wish to seek shelter, have citizenship, study or want to work in Sweden. In recent time there has been a large increase in applications and the time for which a decision is made has increased. Each type of application (such as citizenship) is a process consisting of several stages. How the decision is going through these steps is called flow. The Swedish Migration Board would therefore like to increase their flow efficiency. When the decision is made and the person has take part of it but is not satisfied, he can appeal. This is one of the most complex processes at the Board. The aim is to analyze how long this process will take and what steps in the process affects the time. One step (which was later found to have a significant effect on time) is opinions. This is when the court requests information on what the person is appealing has to say about why he is appealing. To analyze this, two methods were relevant, accelerated failure time (AFT) and the multi-state models (MSM). One can predict time to event (AFT), the other to analyze the effect of time-manipulation (MSM) in the flow. Opinions early in the process is crucial to how quickly an appeal get judgment while the number of opinions increases the time enormously. There are other factors that affect the time but not so much as opinions. The flow efficiency can be increased by taking time to write an informative opinion which allows the court need not to ask for more opinions.

In the past decade, the design and manufacturing of intelligent multipurpose underwater vehicles has increased significantly. In the wide range of studies conducted in this field, the flexibility and autonomy of these devices with respect to their intended performance had been widely investigated. This work is related to the design and manufacturing of a small and lightweight autonomous underwater vehicle (AUV) with vision capabilities allowing detecting and contouring obstacles. It is indeed an exciting challenge to build a small and light submarine AUV, while making tradeoffs between performance and minimum available space as well as energy consumption. In fact, due to the ever-increasing in equipment complexity and performance, designers of AUVs are facing the issues of limited size and energy consumption. By using a pair of thrusters capable to rotate 360o on their axis and implementing a mass shifter with a control loop inside the vehicle, this later can efficiently adapt its depth and direction with minimal energy consumption. A prototype was fabricated and successfully tested in real operating conditions (in both pool and ocean). It includes the design and embedding of accurate custom multi-purpose sensors for multi-task operation as well as an enhanced coordinated system between a high-speed processor and accustomed electrical/mechanical parts of the vehicle, to allow automatic controlling its movements. Furthermore, an efficient tracking system was implemented to automatically detect and bypass obstacles. Then, fuzzy-based controllers were coupled to the main AUV processor system to provide the best commands to safely get around obstacles with minimum energy consumption. The fabricated prototype was able to work for a period of three hours with object tracking options and five hours in a safe environment, at a speed of 0.6 m/s at a depth of 8 m.

Made available in DSpace on 2014-10-09T12:50:22Z (GMT). No. of bitstreams: 0 / Made available in DSpace on 2014-10-09T13:58:51Z (GMT). No. of bitstreams: 1 10890.pdf: 10562798 bytes, checksum: 063bd7e321751780a6d96cafecfe45bc (MD5) / Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) / Tese (Doutoramento) / IPEN/T / Instituto de Pesquisas Energeticas e Nucleares - IPEN/CNEN-SP / FAPESP:01/06837-2

Made available in DSpace on 2014-10-09T12:50:22Z (GMT). No. of bitstreams: 0 / Made available in DSpace on 2014-10-09T13:58:51Z (GMT). No. of bitstreams: 1 10890.pdf: 10562798 bytes, checksum: 063bd7e321751780a6d96cafecfe45bc (MD5) / Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) / Tese (Doutoramento) / IPEN/T / Instituto de Pesquisas Energeticas e Nucleares - IPEN/CNEN-SP / FAPESP:01/06837-2

: Este trabalho tem como objeto o redirecionamento na política externa (RPE) - conceituado como as mudanças mais radicais, abrangentes e rápidas em política externa. Para analisar este fenômeno, são buscadas as principais condições conjunturais que podem aumentar a chance de ocorrência deste evento. Estas condições estão relacionadas ao conceito de Janela Política, que representa o período em que é rompida a inércia política e os tomadores de decisões têm condições de iniciar um processo de RPE. Objetivo: encontrar e delimitar quais as condições conjunturais que aumentam as chances de ocorrência de um RPE. Método: são utilizadas ferramentas metodológicas qualitativas e quantitativas. No segundo capítulo, a análise é feita por meio de um modelo de sobrevivência (Cox Proportional Hazard Model) que analisa o efeito das variáveis sobre os riscos de ocorrência do evento em foco, definido como as alterações mais extremas de comportamento nas votações da Assembleia Geral das Nações Unidas. No terceiro capítulo, é desenvolvida uma análise qualitativa histórica focando especificamente nos casos mais radicais de RPE, buscando identificar padrões comuns no desencadeamento dos processos em estudo; com base nestes casos, são desenvolvidas tipologias explicativas para identificar diferentes caminhos causais que levam ao evento em tela. Resultados: foi identificado que mudanças de regime e de líder político, no âmbito doméstico, e intervenções militares de potências estrangeiras aumentam os riscos de ocorrência de RPE; adicionalmente, a alta polarização política e a mudança de regime, a crise política doméstica com envolvimento de atores internacionais, os processos de isolamento internacional com imposição de sanções econômicas e os períodos de crise econômica com questionamento do modelo econômico vigente por parte dos atores políticos podem combinadamente levar à ocorrência de RPE. Conclusões: apesar da importância do interesses de atores políticos em empreender um projeto de RPE, foi identificado que determinados eventos aumentam os riscos deste processo ocorrer. / This thesis object is the foreign policy restructuring (FPR) - conceptualized as the most radical, encompassing, and fast changes in foreign policy. To analyze this phenomenon, there will be sought the main conjuncture conditions that might enhance the chances of this event occurrence. These conditions are related to the Policy Window concept, that represents a period during which the political inertia is disrupted and decision makers have the circumstances to undertake a FPR process. Objective: find and outline the conjectural conditions and variables that increase the chances of occurrence of a FPR. Methods: it will be used qualitative and quantitative methodological tools. In the second chapter, a survival model (Cox Proportional Hazard Model) analyses the effect variables related to the Policy Window concept over the risks of happening a FPR, defined as the most extreme changes of behavior in United Nations General Assembly roll-call votes. In the third chapter, a historical qualitative analysis is undertaken focusing exclusively on the most radical cases of FPR to develop explanatory typologies in order to identify causal conjunctures and common patters that lead to the outcome. Results: we identified that regime and political leader changes, in the national context, and military interventions by foreign powers enhance the risks of FPR occurrence; additionally, high political polarization combined with regime change, political crisis with international forces involvement, processes of international isolation with economic sanctions enforcement, and economic crises with political actors questioning the current economic model might be combined, configuring causal paths to a FPR. Conclusion: despite the importance of main political actors interest in implementing a FPR process, we identified that specific conjunctures and events raise the risks of a positive outcome.

On s'intéresse à la construction et l'estimation - à partir d'observations incomplètes - de modèles de variables aléatoires à valeurs réelles sur un graphe. Ces modèles doivent être adaptés à un problème de régression non standard où l'identité des variables observées (et donc celle des variables à prédire) varie d'une instance à l'autre. La nature du problème et des données disponibles nous conduit à modéliser le réseau sous la forme d'un champ markovien aléatoire, choix justifié par le principe de maximisation d'entropie de Jaynes. L'outil de prédiction choisi dans ces travaux est l'algorithme Belief Propagation - dans sa version classique ou gaussienne - dont la simplicité et l'efficacité permettent son utilisation sur des réseaux de grande taille. Après avoir fourni un nouveau résultat sur la stabilité locale des points fixes de l'algorithme, on étudie une approche fondée sur un modèle d'Ising latent où les dépendances entre variables réelles sont encodées à travers un réseau de variables binaires. Pour cela, on propose une définition de ces variables basée sur les fonctions de répartition des variables réelles associées. Pour l'étape de prédiction, il est nécessaire de modifier l'algorithme Belief Propagation pour imposer des contraintes de type bayésiennes sur les distributions marginales des variables binaires. L'estimation des paramètres du modèle peut aisément se faire à partir d'observations de paires. Cette approche est en fait une manière de résoudre le problème de régression en travaillant sur les quantiles. D'autre part, on propose un algorithme glouton d'estimation de la structure et des paramètres d'un champ markovien gaussien, basé sur l'algorithme Iterative Proportional Scaling. Cet algorithme produit à chaque itération un nouveau modèle dont la vraisemblance, ou une approximation de celle-ci dans le cas d'observations incomplètes, est supérieure à celle du modèle précédent. Cet algorithme fonctionnant par perturbation locale, il est possible d'imposer des contraintes spectrales assurant une meilleure compatibilité des modèles obtenus avec la version gaussienne de Belief Propagation. Les performances des différentes approches sont illustrées par des expérimentations numériques sur des données synthétiques. / In this work, we focus on the design and estimation - from partial observations - of graphical models of real-valued random variables. These models should be suited for a non-standard regression problem where the identity of the observed variables (and therefore of the variables to predict) changes from an instance to the other. The nature of the problem and of the available data lead us to model the network as a Markov random field, a choice consistent with Jaynes' maximum entropy principle. For the prediction task, we turn to the Belief Propagation algorithm - in its classical or Gaussian flavor - which simplicity and efficiency make it usable on large scale networks. After providing a new result on the local stability of the algorithm's fixed points, we propose an approach based on a latent Ising model, where dependencies between real-valued variables are encoded through a network of binary variables. To this end, we propose a definition of these variables using the cumulative distribution functions of the real-valued variables. For the prediction task, it is necessary to modify the Belief Propagation algorithm in order to impose Bayesian-like constraints on marginal distributions of the binary variables. Estimation of the model parameters can easily be performed using only pairwise observations. In fact, this approach is a way to solve the regression problem by working on quantiles.Furthermore, we propose a greedy algorithm for estimating both the structure and the parameters of a Gauss-Markov random field based on the Iterative Proportional Scaling procedure. At each iteration, the algorithm yields a new model which likelihood, or an approximation of it in the case of partial observations,is higher than the one of the previous model. Because of its local perturbation principle, this algorithm allows us to impose spectral constraints, increasing the compatibility with the Gaussian Belief Propagation algorithm. The performances of all approaches are empirically illustrated on synthetic data.

Master of Science / Department of Statistics / James J. Higgins / The time for an event to take place in an individual is called a survival time. Examples include the time that an individual survives after being diagnosed with a terminal illness or the time that an electronic component functions before failing. A popular parametric model for this type of data is the Weibull model, which is a flexible model that allows for the inclusion of covariates of the survival times. If distributional assumptions are not met or cannot be verified, researchers may turn to the semi-parametric Cox proportional hazards model. This model also allows for the inclusion of covariates of survival times but with less restrictive assumptions. This report compares estimates of the slope of the covariate in the proportional hazards model using the parametric Weibull model and the semi-parametric Cox proportional hazards model to estimate the slope. Properties of these models are discussed in Chapter 1. Numerical examples and a comparison of the mean square errors of the estimates of the slope of the covariate for various sample sizes and for uncensored and censored data are discussed in Chapter 2. When the shape parameter is known, the Weibull model far out performs the Cox proportional hazards model, but when the shape parameter is unknown, the Cox proportional hazards model and the Weibull model give comparable results.

Background: The study examined the effects of the determinants of under-five mortality in Malawi. It therefore aimed to estimate the rate or prevalence of under-five mortality in Malawi and to examine differentials in infant and child mortality by socio-economic, demographic, environmental, health-seeking behaviour and nutritional value. Methods: This study involved a secondary data analysis of the 2010 Malawi Demographic and Health Survey (MDHS) data set of children under five years old and women who had given birth in the five years preceding the survey. The Kaplan-Meier survival analysis and multivariate hazard analysis were used to examine the relationship between under-five mortality and socio-economic. demographic, environmental, health-seeking behaviour and nutritional factors. Results: The results show that birth order, mother's education, place of residence. region and exclusive breastfeeding were significantly associated with under-five mortality. The results also show that there was no significant association between under-five mortality and other indicators of socio-economic. demographic. environmental, health-seeking behaviour. The results also show that more deaths of under-fives occurred during infancy than during childhood. Conclusion: The results show that more deaths occurred during the first months after birth than after 12 months of age. This showed that mother's education, birth order, place of residence, region and breastfeeding had a greater influence on the survival of the child. / Thesis (M.Soc.Sc. Population Studies) North-West University, Mafikeng Campus, 2014