Nas metodologias de mapeamento de QTLs tradicionais, a relação de causalidade entre os caracteres fenotípicos e QTLs normalmente não são consideradas. O desenvolvimento deste trabalho contou com a utilização de dados longitudinais de crescimento de progênies oriundas do cruzamento entre os parentais PB217 e PR255 de um plantio de seringueira, localizado em uma área com dois períodos bem definidos ao longo do ano (altas e médias temperaturas; altas e baixas taxas precipitação). O experimento contém 4 medidas de incremento em diâmetro e altura, que são componentes periódicos do crescimento total da cultura, mensurados em um intervalo de dois anos (entre os 18 aos 52 meses de idade das plantas), sendo dois períodos em estação climática favorável ao desenvolvimento e dois em estação desfavorável, intercalados. Dessa forma foram estudados os parâmetros de relacionamento fenotípico e genético com objetivo de construir um diagrama de arquitetura genética que pondere relações de causalidade. Para modelar os dados fenotípicos foi realizado um elaborado modelo multi-caracteres que contemplou a variação espacial das parcelas experimentais e a variação entre os períodos de medição. Para tanto, foram ajustadas matrizes de variância-covariância (VCOV) adequadas à realidade dos dados, e incorporados dados meteorológicos que descrevessem cada um dos períodos. A partir destes modelos, os valores genotípicos ajustados foram utilizados na detecção dos QTLs. Posteriormente, fenótipos e genótipos foram articulados em um diagrama causal estrutural capaz de inferir sobre padrões genéticos de comportamento de crescimento da cultura. Foram mapeados um total de 13 QTLs, sendo que dois deles foram coincidentes para componentes periódicos de diâmetro nos períodos de estação desfavorável. Foi possível identificar efeitos aditivos e devido à dominância interessantes para o desenvolvimento em períodos de menores temperaturas, apontar o parental PR255 como portador de alelos importantes no desenvolvimento em clima adverso, estimar efeitos indiretos de QTLs não mapeados para determinadas características e explicar o padrão comportamental de crescimento no período em que as progênies foram avaliadas. Esta abordagem demonstrou-se proficiente para utilização em programas melhorando genético assistido por marcadores, por agregar informações pertinentes à seleção dos melhores materiais genéticos. / In traditional methodologies of QTL mapping, the causal relationship between phenotypic characters and QTLs are usually not considered. The development of this work involved the use of longitudinal growth data of progenies from parental PR255 and PB217 of a rubber tree plantation, located in an area with two periods of high and medium temperature and low and high precipitation rates well defined throughout the year. The experiment contains four measures of increment of diameter and height, which are periodic growth components of the total crop growing at an interval of two years (from 18 to 52 months old plants), two periods in a favorable climate station and two in a adverse station, intercalated. Was studied the parameters of phenotypic and genetic relationships in order to construct a diagram of genetic architecture to examine these causal relationships. A multi-trait-multi-occasion model that take into consideration spatial variation and climatic variation was developed. It also contains a variation-covariation matrix with appropriate to the reality of the data were adjusted and incorporated meteorological data was conducted to describe each of the periods. From these models the adjusted genotypic values were used in the detection of QTLs and later phenotypes and genotypes were linked in a structural causal diagram to infer about the genetic patterns of behavior. A total of 13 QTLs were mapped to the periodic growth components and total growth. The genetic architecture was able to identify additive effects and effects due dominance interesting to the development in periods of lower temperatures and drought, pointing parental PR255 as carrier of important alleles to development in adverse weather, estimating indirect effects of QTLs that were not mapped to certain characteristics and explain the physiological behavior pattern of growth in the period in which progenies were evaluated. This approach proved to be proficient to use in breeding programs aiming to implement marker assisted selection.

Le travail présenté traite la question quelle architecture hybride est la plus adapté pour quel type de véhicule. Une approche multi-architecture/multi-application capable d’identifier l’architecture hybride plus efficace en énergie qui considère à la fois les components clés (batterie, moteur électrique, moteur à combustion interne) et la commande optimale, est présenté. La base de cette modélisation est la représentation énergétique macroscopique (REM), qui est combiné avec la programmation orienté objet (POO) afin d’améliorer la modularité et la réutilisation. Les résultats obtenus montrent que des architectures hybrides différents sont le plus adaptés pour différentes applications. De plus, la robustesse des résultats en utilisant des approches de contrôle en temps réel sont étudiés, montrant l’importance de la stratégie de commande. Les résultats obtenus contribuent à la simplification et l’harmonisation de la conception des solutions hybrides pour des applications multiples. / The presented work deals with the question which hybrid architecture is most adapted for which type of vehicle. Therefore, a multi-architecture/multi-application approach capable to identify the most energy efficient hybrid architecture considering both the dimensions of key components (battery, electric motor, internal combustion engine) and the optimal control is presented. Basis of the model is the energetic macroscopic representation (EMR), which has been combined with object oriented programming (OOP) in order to enhance its modularity and reuse capabilities. The obtained results show, that different hybrid architectures are most adapted for different applications. Moreover, the robustness of the results using real time control algorithms are studied, showing that control strategy matters. The obtained results contribute to simplify and harmonize the design of hybrid solutions for multiple applications.

Background: This research aims to explore the recommendations of the 2013 Lancet Series on maternal and child nutrition in the case study of Yemen (2013-2014), by answering the question “What mix of public interventions works best in a given context to reduce child stunting prevalence?” Yemen was selected due to its Government commitment to use a multi-sectoral approach in its planning and financing cycle for nutrition. Method: The research applied a mixed method, starting with a literature review and a cross-country secondary-data analysis to produce evidence for composing a research framework for Yemen. Subsequently, a descriptive analysis, two types of regressions (Probit and Poisson) and an adapted ‘Delphi method’ for discussion with decision-makers from various sectors were carried out. Results: Based on the descriptive analysis, Yemen progressed in: maternal and child health care, drinking water supply and sanitation, girls’ education, delayed marriage and pregnancy. However, infant and young child feeding practices remained inadequate. Significant determinants of child stunting identified by the regressions included characteristics of: child (age, gender and diet diversity), mother (undernutrition, birth-spacing and head of family) and household (access to water and sanitation). Children of households that engaged in agriculture, livestock and fishing were the most likely to access diet diversity and animal-protein sources. Other significant determinants of child diet included maternal education, per capita expenditure, income-related shocks and ownership of a cooking stove and fridge. Results: from the adapted ‘Delphi-method’ discussion showed that decision-makers were ready to use multi-sectoral approaches to converge their existing interventions in the most vulnerable geographical areas. However, they were less keen to retarget beneficiaries based on age, gender or livelihoods. Conclusions The research demonstrates how the applied mixed method can provide a comprehensive way to examine child stunting as a multi-sectoral issue, rather than just considering it as a health problem.

Global Navigation Satellite Systems can provide position, velocity and time information to users using receiver hardware. The United States developed Global Positioning System (GPS) is the only current fully operational system; however further systems are in development. The GPS has shown considerable success for navigation, but it still has a number of problems that limit its accuracy. The two main problems are the ionosphere and local environment of the receiver. The ionosphere causes a delay and random rapid shifts in phase and amplitude (scintillation) to the signal. The local environment can provide the signal with multiple routes (multi-path) to the receiver. In this project a GPS signal simulator is developed, which models the effects of the ionosphere and multi-path on the modulated signals. The focus is made on the GPS system as the simulator measurements can be compared to the real measurements; however other systems will be considered in the future. A number of experiments investigating multi-path and ionospheric effects on a receiver’s ability to track the signals have been completed. The simulator has been used to replicate a real local multi-path environment and the results have been compared. Further investigations of the multi-path have shown a unique multi-path signature in the receiver power output. The later part of the thesis describes a case study investigating a short but rapid period of scintillation observed on three receivers based in Norway. An analysis of the multi-path environment was completed, but was found not to be the cause. The ionosphere was investigated using equipment based across Scandinavia. The equipment showed that geomagnetic conditions were disturbed at the time of the event. The GPS measurements were compared with all-sky camera data to show that the scintillation can be attributed to the GPS signal path crossing electron density structures associated with the aurora.

"The real-time detection of anomalous phenomena on streaming data has become increasingly important for applications ranging from fraud detection, financial analysis to traffic management. In these streaming applications, often a large number of similar continuous outlier detection queries are executed concurrently. In the light of the high algorithmic complexity of detecting and maintaining outlier patterns for different parameter settings independently, we propose a shared execution methodology called SOP that handles a large batch of requests with diverse pattern configurations. First, our systematic analysis reveals opportunities for maximum resource sharing by leveraging commonalities among outlier detection queries. For that, we introduce a sharing strategy that integrates all computation results into one compact data structure. It leverages temporal relationships among stream data points to prioritize the probing process. Second, this work is the first to consider predicate constraints in the outlier detection context. By distinguishing between target and scope constraints, customized fragment sharing and block selection strategies can be effectively applied to maximize the efficiency of system resource utilization. Our experimental studies utilizing real stream data demonstrate that our approach performs 3 orders of magnitude faster than the start-of-the-art and scales to 1000s of queries."

Cette thèse traite du problème de l'apprentissage automatique supervisé dans le cas ou l'on considère plusieurs sorties, potentiellement de différent types. Nous proposons d'explorer trois différents axes de recherche en rapport avec ce sujet. Dans un premier temps, nous nous concentrons sur le cas homogène et proposons un cadre théorique pour étudier la consistance des problèmes multi-labels dans le cas de l'utilisation de chaîne de classifieurs. Ensuite, en nous plaçant dans ce cadre, nous proposons une borne de Rademacher sur l'erreur de généralisation pour tous les classifieurs de la chaîne et exposons deux facteurs de dépendance reliant les sorties les unes aux autres. Dans un deuxième temps, nous développons et analysons la performance de modèles en lien avec la théorie proposée. Toujours dans le cadre de l'apprentissage avec plusieurs sorties homogènes, nous proposons un modèle basé sur des réseaux de neurones pour l'analyse de sentiments à grain fin. Enfin, nous proposons un cadre et une étude empirique qui montrent la pertinence de l'apprentissage multi-objectif dans le cas de multiples sorties hétérogènes. / In this thesis, we study the problem of learning with multiple outputs related to different tasks, such as classification and ranking. In this line of research, we explored three different axes. First we proposed a theoretical framework that can be used to show the consistency of multi-label learning in the case of classifier chains, where outputs are homogeneous. Based on this framework, we proposed Rademacher generalization error bound made by any classifier in the chain and exhibit dependency factors relating each output to the others. As a result, we introduced multiple strategies to learn classifier chains and select an order for the chain. Still focusing on the homogeneous multi-output framework, we proposed a neural network based solution for fine-grained sentiment analysis and show the efficiency of the approach. Finally, we proposed a framework and an empirical study showing the interest of learning with multiple tasks, even when the outputs are of different types.

La tâche consistant à tirer de l'information des images d'une caméra au cours du temps pour cartographier l'environnement et se localiser à l'intérieur de celui-ci, est appelée Localisation et Cartographie Simultanée ou SLAM.Développée à la fois par les communautés scientifiques de robotique et vision par ordinateur les applications sont multiples. Des robots bénéficient de cette capacité en gagnant en autonomie. Ces dernières années, des résultats impressionnants ont été obtenus pour des applications à des moyens de transport autonomes.Une autre champ d'application est la réalité augmenté. La localisation donnée par le SLAM offre la possibilité d'obtenir un rendu des éléments virtuels en cohérence avec les mouvements de l'utilisateur. Ainsi le cinéma, les jeux vidéos, le tourisme peuvent bénéficier de techniques SLAM. L'assistance aux travailleurs effectuant des tâches de précision ou répétitives compte également parmi les champs d'application du SLAM. Dans le cadre de cette thèse nous nous sommes intéressés au SLAM dans une optique d'applications réalistes de réalité augmentée. Bien que le sujet ait été beaucoup exploré et que d'intéressants résultats aient été obtenus, la tâche n'est toujours pas parfaitement résolue. Le problème du SLAM est un sujet de recherche ouvert, aussi bien sur des aspects spatiaux (dérive, fermeture de boucle) que temporels (temps de traitement). Dans le cadre du SLAM monoculaire nous avons surtout adressé le problème de la dérive. Puis nous nous sommes intéressés au SLAM multi-capteurs, afin d'adresser le problème des mouvements de rotation problématiques dans le cas monoculaire, et celui de la complexité calculatoire. / Gathering informations from the images of a camera, over time, in order to map the environment and localize the camera in it, is a task refered to as Simultaneous Localization and Mapping, or SLAM. Developped both by the robotics and computer vision scientific communities, its applications are many. Robots gain autonomy from this ability. Quite recently, impressive results have been obtained in applications to autonomous transportation vehicles. Another field of application is augmented reality. The localization offered by SLAM enables us to display virtual objects in a consistent way a user movements. Thus, cinema, video games, tourisme applications can benefit from SLAM methods. Visual aids to workers performing complex or repetetive tasks is also an interesting application of SLAM methods. During this PhD thesis, we took interest in SLAM with the idea of realistic augmented reality applications in mind. Though the topic has been extensively explored and many impressive results obtained, the task isn't completely solved. The problem is still an open one, regarding spatial facets (drift, loop closure) as well as temporal (processing time). As part of our monocular SLAM explorations, we mainly studied the drift issue. We then explored multisensor SLAM, both as a mean to handle problematical rotational movements for the monocular setup and as mean to reduce the substantial processing times needed to solve the problem.

Tese de mestrado. Engenharia Mecânica. Faculdade de Engenharia. Universidade do Porto, Universidade de Bristol. 2005

Tese de mestrado integrado. Engenharia Informática e Computação. Faculdade de Engenharia. Universidade do Porto. 2012

Multi-level security is prevalent within the military; however, the private sector has not yet invested in the approach. As big data, Internet of things, and artificial intelligence drive businesses to collaborate (share data, algorithms, and tools) the need to secure such resources while simultaneously sharing them will push towards an alternative approach-–namely Multi-level security. The military labels data according to the sensitivity it carries as related to national security. Furthermore, the military restricts access by both the overall trust in the individual and by their need-to-know. To put it another way, data has a certain level of sensitivity and only those individuals that can be trusted with the data and have a need-to-know shall have access to such data. Military organizations not only limit access to digital data but also to sensitive discussions, often having sensitive talks within a Sensitive Compartmented Information Facility referred to as a SCIF. Irrespective of the media, all data must be secured and disseminated in order to produce value. Inaccessible data has no real value, as data must be accessible in order to be actionable and produce value. Along the same lines, data often requires aggregation to become actionable. Creating a security domain with multiple levels of trust and need-to-know ensures that data can both be accessed and aggregated. Multi-level secure domains exist in military organizations today, however, the challenge arises when two domains want to share data—hence the need for multi-level secure data dissemination. One way to accomplish this objective is for Domain X to contact Domain Y and together identify how their two security domains can map to one another. After determining the mapping Domain X can send Domain Y data, however, what if Domain Z wants access to the same data? Should Domain Z request the data from Domain Y? Would Domain Y violate the trust of Domain X, if Domain Y disseminates the data? Perhaps, Domain Z is only cleared to a portion of the data. These are the issues related to the dissemination of MLS data within a multi-domain environment. The objective of this project is to propose a solution that would allow domains to securely disseminate data without the need to repackage the data for each domain. The solution outlined in this project, leverages Simple Public Key certificates, Active Bundle, and a directory server. When combined, the three technologies allow domains: to convey both trust and authorization policies, learn about trust and authorization policies of external domains, and provide a mechanism to securely disseminate data.