In this thesis we study three basic issues related to international black tea markets: Are black tea markets integrated? Where is the price of black tea discovered? Are there leaders and followers in black tea markets? We use two statistical techniques as engines of analysis. First, we use time series methods to capture regularities in time lags among price series. Second, we use directed acyclic graphs to discover how surprises (innovations) in prices from each market are communicated to other markets in contemporaneous time. Weekly time series data on black tea prices from seven markets around the world are studied using time series methods. The study follows two paths. We study these prices in a common currency, the US dollar. We also study prices in each country's local currency. Results from unit root tests suggest that prices from three Indian markets are not generated through random walk-like behavior. We conclude that the Indian markets are not weak form efficient. However, prices from all non-Indian markets cannot be distinguished from random walk-like behavior. These latter markets are weak form efficient. Further analysis on these latter markets is conducted to determine whether information among the markets is shared. Vector Autoregressions (VARs) on the non-Indian markets are studied using directed acyclic graphs, impulse response functions and forecast error decomposition analyses. In both local currencies and dollar-converted series, the Sri Lankan and Indonesian markets are price leaders in contemporaneous time. Kenya is an information sink. It is endogenous in current time. Malawi is an exogenous price leader in dollar terms, but it is endogenous in local currency in contemporaneous time. In the long run, Sri Lanka, Indonesia and Malawi are price leaders in US dollar terms. In local currency series, Indonesia, Kenya and Malawi are price leaders in the long run. We use Theil's U-statistic to test the forecasting ability of the VAR models. We find for most markets in either dollars or on local currencies that a random walk forecast outperforms the VAR generated forecasts. This last result suggests the non-Indian markets are both weak form and semi-strong form efficient.

Tuberculosis (TB) is called a disease of poverty and is the main cause of death from infectious diseases among adults. In 1993 the World Health Organisation (WHO) declared TB to be a global emergency; however there were still approximately 1.4 million deaths due to TB in 2011. This thesis contains a detailed study of the existing literature regarding the global risk factors of TB. The risk factors identified from the literature review search which were also available from the NFHS-3 survey were then analysed to determine how well we could identify respondents who are at high risk of TB. We looked at the stigma and misconceptions people have regarding TB and include detailed reports from the existing literature of how a persons wealth, health, education, nutrition, and HIV status affect how likely the person is to have TB. The difference in the risk factor distribution for the TB and non-TB populations were examined and classification trees, nearest neighbours, and logistic regression models were trialled to determine if it was possible for respondents who were at high risk of TB to be identified. Finally gender-specific statistically likely directed acyclic graphs were created to visualise the most likely associations between the variables.

<p>In knowledge-based engineering, the inference engine plays an important part in the behaviour of the system. A flexible and adaptive execution scheme allows the designer to experiment with different modes of operation and selecting an appropriate one with respect to the initial data set and the execution goal.</p><p>In this project, an extension of an existing research prototype software in the field of knowledge-based engineering will be developed, with the goal of building a reliable and easy to use dependency resolution engine that will replace a less-than-ideal current implementation of the same. A discussion will be included how the knowledge concepts and objects can be represented in an abstract mathematical form, converting at the same time the problem of dependency resolution to a more formally specified one in terms of the data abstraction proposed. Some algorithms and methods that are used to operate on the data set will be discussed from both a theoretical and programming point of view, analysing their complexity, proposing and testing their implementation. Graphical interface controls that can be used to visualize and understand easily the relations in the available knowledge base will be also demonstrated.</p><p>The testing and verification of the resulting software will be presented, comparing its behaviour against reference tools serving similar purposes. Methods for validating the consistency of the knowledge base will also be discussed. Finally, the integration of the newly-developed code within the context of the prototype will be discussed, commenting on the new features and functionality gained.</p>

In knowledge-based engineering, the inference engine plays an important part in the behaviour of the system. A flexible and adaptive execution scheme allows the designer to experiment with different modes of operation and selecting an appropriate one with respect to the initial data set and the execution goal. In this project, an extension of an existing research prototype software in the field of knowledge-based engineering will be developed, with the goal of building a reliable and easy to use dependency resolution engine that will replace a less-than-ideal current implementation of the same. A discussion will be included how the knowledge concepts and objects can be represented in an abstract mathematical form, converting at the same time the problem of dependency resolution to a more formally specified one in terms of the data abstraction proposed. Some algorithms and methods that are used to operate on the data set will be discussed from both a theoretical and programming point of view, analysing their complexity, proposing and testing their implementation. Graphical interface controls that can be used to visualize and understand easily the relations in the available knowledge base will be also demonstrated. The testing and verification of the resulting software will be presented, comparing its behaviour against reference tools serving similar purposes. Methods for validating the consistency of the knowledge base will also be discussed. Finally, the integration of the newly-developed code within the context of the prototype will be discussed, commenting on the new features and functionality gained.

This dissertation examines several issues regarding the congestion on the Upper Mississippi River and Illinois Waterway. Chapter II identifies and measures the impact of lock congestion on grain barge rates on these waterways. Results indicate grain barge rates on both rivers are not affected by lagged lock congestion. In present time, however, lock congestion in the lower reaches of the upper Mississippi and Illinois Rivers are found to increase barge rates that link the north central United States to the lower Mississippi Gulf port area. The findings suggest the impact of lock congestion on grain barge rates is moderate. Chapter III explores the interaction between grain prices in export and domestic markets and transportation rates linking these markets over time. Three model frameworks were evaluated and some consistent results are observed. In general, shocks in transportation rates (barge, rail, and ocean) explain a great proportion of the variation in corn and soybean market prices in the long run, suggesting the importance of transportation in grain price determination. The volatile ocean freight rates are the mostimportant transportation rates contributing to the variation in grain prices, while shocks in barge rates on the Upper Mississippi River and Illinois Waterway generally explain less than 15 percent of the variation in grain prices. The dynamic interrelationships among the six evaluated transportation rates are also found. In addition, the north central corn markets likely have the most influence over other markets while soybean export price dominates the soybean market in the long run. Chapter IV estimates the structural demand for grain barge transportation on both the upper Mississippi and Illinois Rivers. Results suggest foreign grain demand is the most influential force affecting grain barge demand on both rivers. Also, results indicate an inelastic demand for grain barge transportation on the Upper Mississippi in the short run; demand is price elastic in the long run. The price elasticity for grain barge demand on the Illinois River is consistently inelastic. Additionally, the winter season and floods affect demand on the Upper Mississippi negatively, while barge demand increases on the Illinois River in winter.

Les applications temps réel durs sont celles qui doivent exécuter en respectant des contraintes temporelles. L'ordonnancement temps réel a bien été étudié sur mono-processeurs depuis plusieurs années. Récemment, l'utilisation d'architectures multiprocesseurs a augmenté dans les applications industrielles et des architectures parallèles sont proposées pour que le logiciel devienne compatible avec ces plateformes. L'ordonnancement multiprocesseurs de tâches parallèles dépendantes n'est pas une simple généralisation du cas mono-processeur et la problématique d'ordonnancement devient plus complexe et difficile.
Dans cette thèse, nous étudions le problème d'ordonnancement temps réel de graphes de tâches parallèles acycliques sur des plateformes multiprocesseurs. Dans ce modèle, un graphe est composé d'un ensemble de sous-tâches dépendantes sous contraintes de précédence qui expriment les relations de précédences entre les sous-tâches. L'ordre d'exécution des sous-tâches est dynamique, c'est-à-dire que les sous-tâches peuvent s'exécuter en parallèle ou séquentiellement par rapport aux décisions de l'ordonnanceur temps réel. Pour traiter les contraintes de précédence, nous proposons deux méthodes pour l'ordonnancement des graphes : par transformation du modèle de graphe de sous tâches parallèles en un modèle de tâches séquentielles indépendantes, plus simple à ordonnancer et par ordonnancement direct des graphes en prenant en compte les relations de dépendance entre les sous-tâches. Nous proposons un ordonnancement des graphes en prenant directement en compte les paramètres temporels des graphes et un ordonnancement au niveau des sous-tâches, par rapport à des paramètres temporels attribués aux sous-tâches par un algorithme spécifique.
Enfin, nous prouvons que les deux méthodes d'ordonnancement de graphes ne sont pas comparables. Nous fournissons alors des résultats de simulation pour comparer ces méthodes en utilisant les algorithmes d'ordonnancement globaux EDF et DM. Nous avons développé un logiciel nommé YARTISS pour générer des graphes aléatoires et réaliser les simulations / The interest for multiprocessor systems has recently been increased in industrial applications, and parallel programming API's have been introduced to benefit from new processing capabilities. The use of multiprocessors for real-time systems, whose execution is performed based on certain temporal constraints is now investigated by the industry. Real-time scheduling problem becomes more complex and challenging in that context. In multiprocessor systems, a hard real-time scheduler is responsible for allocating ready jobs to available processors of the systems while respecting their timing parameters.
In this thesis, we study the problem of real-time scheduling of parallel Directed Acyclic Graph (DAG) tasks on homogeneous multiprocessor systems. In this model, a DAG task consists of a set of subtasks that execute under precedence constraints. At all times, the real-time scheduler is responsible for determining how subtasks execute, either sequentially or in parallel, based on the available processors of the system. We propose two DAG scheduling approaches to determine the execution form of DAG tasks. The first approach is the DAG Stretching algorithm, from the Model Transformation approach, which forces DAG tasks to execute as sequentially as possible. The second approach is the Direct Scheduling, which aims at scheduling DAG tasks while respecting their internal dependencies. We provide real-time schedulability analyses for Direct Scheduling at DAG-Level and at Subtask-Level.
Due to the incomparability of DAG scheduling approaches, we use extensive simulations to compare performance of global EDF with global DM scheduling using our simulation tool YARTISS

L’utilisation des mesures subjectives en épidémiologie s’est intensifiée récemment, notamment avec la volonté de plus en plus affirmée d’intégrer la perception qu’ont les sujets de leur santé dans l’étude des maladies et l’évaluation des interventions. La psychométrie regroupe les méthodes statistiques utilisées pour la construction des questionnaires et l’analyse des données qui en sont issues. Ce travail de thèse avait pour but d’explorer différents problèmes méthodologiques soulevés par l’utilisation des techniques psychométriques en épidémiologie. Trois études empiriques sont présentées et concernent 1/ la phase de validation de l’instrument : l’objectif était de développer, à l’aide de données simulées, un outil de calcul de la taille d’échantillon pour la validation d’échelle en psychiatrie ; 2/ les propriétés mathématiques de la mesure obtenue : l’objectif était de comparer les performances de la différence minimale cliniquement pertinente d’un questionnaire calculée sur des données de cohorte, soit dans le cadre de la théorie classique des tests (CTT), soit dans celui de la théorie de réponse à l’item (IRT) ; 3/ son utilisation dans un schéma longitudinal : l’objectif était de comparer, à l’aide de données simulées, les performances d’une méthode statistique d’analyse de l’évolution longitudinale d’un phénomène subjectif mesuré à l’aide de la CTT ou de l’IRT, en particulier lorsque certains items disponibles pour la mesure différaient à chaque temps. Enfin, l’utilisation de graphes orientés acycliques a permis de discuter, à l’aide des résultats de ces trois études, la notion de biais d’information lors de l’utilisation des mesures subjectives en épidémiologie. / Recently, subjective measurements have increasingly been used in epidemiology, alongside the growing will to integrate individuals’ point of view on their health in studies on diseases or health interventions. Psychometrics includes statistical methods used to develop questionnaires and to analyze questionnaire data. This doctoral dissertation aimed to explore methodological issues raised by the use of psychometric techniques in epidemiology. Three empirical studies are presented and cover 1 / the validation stage of a questionnaire: the objective was to develop, using simulated data, a tool to determine sample size for internal validity studies on psychiatric scale; 2 / the mathematical properties of the subjective measurement: the objective was to compare the performances of the minimal clinically important difference of a questionnaire, assessed on data from a cohort study, computed using the classical test theory (CTT) framework or the item response theory framework (IRT); 3 / its use in a longitudinal design: the objective was to compare, using simulated data, the performances of a statistical method aimed to analyze the longitudinal course of a subjective phenomenon measured using the CTT or IRT framework, especially when some of the available items used for its measurement differ at each time of data collection. Finally, directed acyclic graphs were used to discuss the results from these three studies and the concept of information bias when subjective measurements are used in epidemiology.

Η παρούσα διπλωματική έχει ως σκοπό να συνδέσει την λειτουργία υπάρχοντος ορθογράφου με συγκεκριμένη δομή αποθήκευσης και αναζήτησης λέξεων. Κριτήρια του ορθογράφου είναι να είναι ανοιχτού κώδικα και σκοπός είναι να του προστεθεί η δυνατότητα να λειτουργεί με ακυκλικούς γράφους, ντετερμινιστικούς ή μη. Τα πλεονεκτήματα της νέας δομής και λειτουργίας του ορθογράφου είναι πολλαπλά και παρουσιάζονται στη πορεία της διπλωματικής. Αν και οι δοκιμές που έγιναν, δεν αναδεικνύουν τα πλεονεκτήματα αυτά, σε θεωρητικό επίπεδο η εξέλιξη μπορεί να είναι μεγάλη, και σε ταχύτητα αλλά και σε απόδοση. / Target of this project is to connect the proccess of an existing speller to a spesific structure of storing and searching words. Basic criteria of this speller are: open source, capability to work with acyclic graphs, deteministic or not. The advantages of this new structure and proccess of the speller are presented in this project.

To achieve economic development, regional authorities have to address issues that relate to climate change, efficient information flow in the market place, and health care. This dissertation presents three essays on current issues of concern to economic development in Africa. Climate change is examined in terms of its effects on the Egyptian agricultural sector; transmission of world price to small scale growers is examined in Uganda; and the benefits of insecticide-treated bed nets use is examined in Africa. In essay I, to address the impact of climate change on the Egyptian agricultural sector under alternative population growth rates, water use and crop yield assumption; the Egyptian Agricultural Sector Model (EASM) is updated and expanded to improve hydrological modeling and used to portray agricultural activity and hydrological flow. The results indicate that climate change will cause damages (costs) to the Egyptian agricultural sector and these will increase over time. Egypt may reduce these future damages by controlling its population growth rate and using water conservation strategies. In essay II, I use vector autoregressive analysis to examine the transmissions of price information to Uganda coffee growers; using monthly coffee price data on retail, futures, farmgate and world prices from 1994 to 2010. Improved transmission of world prices to farmers may increase their decision making to obtain a better market price. Directed acyclic graphs reveal that there is a causal flow of information from the indicator price to the London futures price to the Uganda grower?s price in contemporaneous time. Forecast error variance decomposition indicates that at moving ahead 12 months, the uncertainty in Uganda grower price is attributable to the indicator price (world spot price), own price (farmgate), London future and Spain retail price in rank order. In essay III, the cost of malaria in children under five years and the use of insecticide treated bed nets is examined in the context of 18 countries in Africa. I examine the direct and indirect cost of malaria in children under five years and the benefit of investing in insecticide treated mosquito nets as a preventative strategy in 18 African countries. The results indicate that the use of mosquito treated nets reduces the number of malaria cases in children; and this can induce 0.5% reduction in outpatient treatment costs, 11% reduction in inpatient treatment costs, 11% reduction in productivity loss, and 15% reduction in disability adjusted life years (DALY) annually.

Relational data is characterised by the rich structure it encodes in the dependencies between the individual entities of a given domain. Statistical Relational Learning (SRL) combines first-order logic and probability to learn and reason over relational domains by creating parametric probability distributions over relational structures. SRL models can succinctly represent the complex dependencies in relational data and admit learning and inference under uncertainty. However, these models are significantly limited when it comes to the tractability of learning and inference. This limitation emerges from the intractability of Weighted First Order Model Counting (WFOMC), as both learning and inference in SRL models can be reduced to instances of WFOMC. Hence, fragments of first-order logic that admit tractable WFOMC, widely known as domain-liftable, can significantly advance the practicality and efficiency of SRL models. Recent works have uncovered another limitation of SRL models, i.e., they lead to unintuitive behaviours when used across varying domain sizes, violating fundamental consistency conditions expected of sound probabilistic models. Such inconsistencies also mean that conventional machine learning techniques, like training with batched data, cannot be soundly used for SRL models. In this thesis, we contribute to both the tractability and consistency of probabilistic inference in SRL models. We first expand the class of domain-liftable fragments with counting quantifiers and cardinality constraints. Unlike the algorithmic approaches proposed in the literature, we present a uniform combinatorial approach, admitting analytical combinatorial formulas for WFOMC. Our approach motivates a new family of weight functions allowing us to express a larger class of probability distributions without losing domain-liftability. We further expand the class of domain-liftable fragments with constraints inexpressible in first-order logic, namely acyclicity and connectivity constraints. Finally, we present a complete characterization for a statistically consistent (a.k.a projective) models in the two-variable fragment of a widely used class of SRL models, namely Markov Logic Networks.