abstract: The process of combining data is one in which information from disjoint datasets sharing at least a number of common variables is merged. This process is commonly referred to as data fusion, with the main objective of creating a new dataset permitting more flexible analyses than the separate analysis of each individual dataset. Many data fusion methods have been proposed in the literature, although most utilize the frequentist framework. This dissertation investigates a new approach called Bayesian Synthesis in which information obtained from one dataset acts as priors for the next analysis. This process continues sequentially until a single posterior distribution is created using all available data. These informative augmented data-dependent priors provide an extra source of information that may aid in the accuracy of estimation. To examine the performance of the proposed Bayesian Synthesis approach, first, results of simulated data with known population values under a variety of conditions were examined. Next, these results were compared to those from the traditional maximum likelihood approach to data fusion, as well as the data fusion approach analyzed via Bayes. The assessment of parameter recovery based on the proposed Bayesian Synthesis approach was evaluated using four criteria to reflect measures of raw bias, relative bias, accuracy, and efficiency. Subsequently, empirical analyses with real data were conducted. For this purpose, the fusion of real data from five longitudinal studies of mathematics ability varying in their assessment of ability and in the timing of measurement occasions was used. Results from the Bayesian Synthesis and data fusion approaches with combined data using Bayesian and maximum likelihood estimation methods were reported. The results illustrate that Bayesian Synthesis with data driven priors is a highly effective approach, provided that the sample sizes for the fused data are large enough to provide unbiased estimates. Bayesian Synthesis provides another beneficial approach to data fusion that can effectively be used to enhance the validity of conclusions obtained from the merging of data from different studies. / Dissertation/Thesis / Doctoral Dissertation Psychology 2017

Les radiations sont omniprésentes. Elles ont de nombreuses applications dans des domaines variés: en médecine, elles permettent de réaliser des diagnostiques et de guérir des patients; en communication, tous les systèmes modernes utilisent des formes de rayonnements électromagnétiques; et en science, les chercheurs les utilisent pour découvrir la composition et la structure des matériaux, pour n'en nommer que quelques-unes. Concrètement, la radiation est un processus au cours duquel des particules ou des ondes voyagent à travers différents types de matériaux. La radiation peut être très énergétique, et aller jusqu'à casser les atomes de la matière ordinaire. Dans ce cas, on parlera de radiation ionisante. Il est communément admis que la radiation ionisante peut être bien plus nocif pour les êtres vivants que la radiation non ionisante. Dans cette dissertation, nous traiterons de la radiation ionisante. La radioactivité est le processus d'émission des radiations ionisantes. Elle existe sous forme naturelle, et est présente dans les sols, dans l'air et notre planète entière est bombardée en permanence de rayonnements cosmiques énergétiques. Depuis le début du XXe siècle, les chercheurs sont capables de créer artificiellement de la matière radioactive. Cette découverte a offert de multiples avancées technologiques, mais a eu également de lourdes conséquences pour l'humanité comme l'ont démontrés les évènements de Tchernobyl et de Fukushima ou d'autres accidents dans le monde médical. Cette dangerosité a conduit à l'élaboration d'un système de radioprotection. Dans la pratique, la radioprotection est principalement mise en œuvre en utilisant la méthode ALARA. Cette méthodologie consiste à justifier, optimiser et limiter les doses reçues. Elle est utilisée conjointement avec les limites légales. Le facteur d'optimisation est contraint par le fait que l'exposition volontaire d'un travailleur aux radiations lors d'une opération doit être plus bénéfique que si aucune intervention humaine n'était conduite dans une situation donnée. Dans le monde industriel et scientifique, il existe des infrastructures qui émettent des rayonnements ionisants. La plupart d'entre elles nécessitent des opérations de maintenance. Dans l'esprit du principe ALARA, ces interventions doivent être optimisées pour réduire l'exposition des travailleurs aux rayonnements ionisants. Cette optimisation ne peut pas être réalisée de manière automatique car la faisabilité des interventions nécessite dans tous les cas une évaluation humaine. La planification des interventions peut cependant être facilitée par des moyens techniques et scientifiques comme par exemple un outil informatique. Dans le contexte décrit ci-dessus, cette thèse regroupe des considérations techniques et scientifiques, et présente la méthodologie utilisée pour développer des outils logiciels pour la mise en œuvre de la radioprotection. / Radiation is omnipresent. It has many interesting applications: in medicine, where it allows curing and diagnosing patients; in communication, where modern communication systems make use of electromagnetic radiation; and in science, where it is used to discover the structure of materials; to name a few. Physically, radiation is a process in which particles or waves travel through any kind of material, usually air. Radiation can be very energetic, in which case it can break the atoms of ordinary matter (ionization). If this is the case, radiation is called ionizing. It is known that ionizing radiation can be far more harmful to living beings than non-ionizing radiation. In this dissertation, we are concerned with ionizing radiation. Naturally occurring ionizing radiation in the form of radioactivity is a most natural phenomenon. Almost everything is radioactive: there is radiation emerging from the soil, it is in the air, and the whole planet is constantly undergoing streams of energetic cosmic radiation. Since the beginning of the twentieth century, we are also able to artificially create radio-active matter. This has opened a lot of interesting technological opportunities, but has also given a tremendous responsibility to humanity, as the nuclear accidents in Chernobyl and Fukushima, and various accidents in the medical world have made clear. This has led to the elaboration of a radiological protection system. In practice, the radiological protection system is mostly implemented using a methodology that is indicated with the acronym ALARA: As Low As Reasonably Achievable. This methodology consists of justifying, optimizing and limiting the radiation dose received. This methodology is applied in conjunction with the legal limits. The word "reasonably" means that the optimization of radiation exposure has to be seen in context. The optimization is constrained by the fact that the positive effects of an operation might surpass the negative effects caused by the radiation. Several industrial and scientific procedures give rise to facilities with ionizing radiation. Most technical and scientific facilities also need maintenance operations. In the spirit of ALARA, these interventions need to be optimized in terms of the exposure of the maintenace workers to ionizing radiation. This optimization cannot be automated since the feasibility of the intervention tasks requires human assessment. The intervention planning could however be facilitated by technical-scientific means, e.g. software tools. In the context sketched above, this thesis provides technical-scientific considerations and the development of technical-scientific methodologies and software tools for the implementation of radiation protection.In particular, this thesis addresses the need for an interactive visual intervention planning tool in the context of high energy particle accelerator facilities.

abstract: Over 2 billion people are using online social network services, such as Facebook, Twitter, Google+, LinkedIn, and Pinterest. Users update their status, post their photos, share their information, and chat with others in these social network sites every day; however, not everyone shares the same amount of information. This thesis explores methods of linking publicly available data sources as a means of extrapolating missing information of Facebook. An application named "Visual Friends Income Map" has been created on Facebook to collect social network data and explore geodemographic properties to link publicly available data, such as the US census data. Multiple predictors are implemented to link data sets and extrapolate missing information from Facebook with accurate predictions. The location based predictor matches Facebook users' locations with census data at the city level for income and demographic predictions. Age and relationship based predictors are created to improve the accuracy of the proposed location based predictor utilizing social network link information. In the case where a user does not share any location information on their Facebook profile, a kernel density estimation location predictor is created. This predictor utilizes publicly available telephone record information of all people with the same surname of this user in the US to create a likelihood distribution of the user's location. This is combined with the user's IP level information in order to narrow the probability estimation down to a local regional constraint. / Dissertation/Thesis / M.S. Computer Science 2012

O crescente volume de informações disponíveis na rede mundial de computadores, gera a necessidade do uso de ferramentas que sejam capazes de localizá-las e ordenálas, de forma cada vez mais precisa e que demandem cada vez menos recursos computacionais. Esta necessidade tem motivado pesquisadores a estudar e desenvolver modelos e técnicas que atendam esta demanda. Estudos recentes têm sinalizado que utilizar vários ordenamentos (rankings) previamente montados possibilita o retorno e ordenação de objetos de qualquer natureza com mais eficiência, principalmente pelo fato de haver uma redução no custo da busca pela informação. Este processo, conhecido como fusão de rankings, permite que se obtenha um ordenamento com base na opinião de diversos juízes (critérios), o que possibilita considerar um grande número de fontes, tanto geradas automaticamente como por especialistas. Entretanto os modelos propostos até então tem apresentado várias limitações na sua aplicação: desde a quantidade de rankings envolvidos até, principalmente, a utilização de rankings parciais. A proposta desta dissertação é apresentar um modelo de fusão de rankings que busca estabelecer um consenso entre as opiniões (rankings) dos diferentes juízes envolvidos, considerando distintos graus de relevância ou importância entre eles. A base desta proposta está na Análise de Preferência, um conjunto de técnicas que permite o tratamento da multidimensionalidade dos dados envolvidos. Ao ser testado em uma aplicação real, o modelo mostrou conseguir suprir algumas limitações apresentadas em outras abordagens, bem como apresentou resultados similares aos das aplicações originais. Esta pesquisa, ainda contribui, com a especificação de um sistema Web baseado em tecnologias open source, o qual permite que qualquer pessoa possa realizar a fusão de rankings. / The growing volume of available information on the web creates the need to use tools that are capable of retrieve and ordering this information, ever more precise and using less computer resources. This need has motivated researchers to study and develop models and techniques that solve this problem. Recent studies have indicated that use multiple rankings previously mounted makes possible the return and sorting of the objects of any kind with more efficiency, mainly because there is a reduction in the cost of searching for information. This process, called ranking fusion, provide a ranking based on the opinion of several judges (criteria), considering a large number of sources, both generated automatically and also by specialists. However the proposed models have shown severe limitations in its application: from the amount involved rankings to the use of partial rankings. The proposal of this dissertation is to show a model of ranking fusion that seeks to establish a consensus between the judgement (rankings) of the various judges involved, considering different degrees of relevance or importance among them. The baseline of this proposal is the Preference Analysis, a set of techniques that allows the treatment of multidimensional data handling. During tests in a real application, the model supplied some limitations presented by other approaches, and presented results similar to the original applications. Additionally, this research contributes with the specification of a web system based on open-sources technologies, enabling the realization of fusion rankings by anyone.

Orientador: Carlos Alberto dos Reis Filho / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Eletrica e de Computação / Made available in DSpace on 2018-08-05T17:36:56Z (GMT). No. of bitstreams: 1 Salustiano_RogerioEsteves_M.pdf: 3698724 bytes, checksum: a5c6d59ec19db38f5a0324243ddb1eb5 (MD5) Previous issue date: 2006 / Resumo: Este trabalho propõe um sistema computacional no qual são aplicadas técnicas de Fusão de Sensores no monitoramento de ambientes. O sistema proposto permite a utilização e incorporação de diversos tipos de dados, incluindo imagens, sons e números em diferentes bases. Dentre os diversos algoritmos pertinentes a um sistema como este, foram implementados os de Sensores em Consenso que visam a combinação de dados de uma mesma natureza. O sistema proposto é suficientemente flexível, permitindo a inclusão de novos tipos de dados e os correspondentes algoritmos que os processem. Todo o processo de recebimento dos dados produzidos pelos sensores, configuração e visualização dos resultados é realizado através da Internet / Abstract: This work proposes a computer system in which Sensor Fusion techniques are applied to monitoring the environment. The proposed system allows the use and incorporation of different data types, including images, sounds and numbers in different bases. Among the existing algorithms that pertain to a system like this, those, which aim to combine data of the same nature, called Consensus Sensors, have been particularly implemented. The proposed system is flexible enough and allows the inclusion of new data types and their corresponding algorithms. The whole process of receiving the data produced by the sensors, configuration of produced results as well as their visualization is performed through the Internet / Mestrado / Eletrônica, Microeletrônica e Optoeletrônica / Mestre em Engenharia Elétrica

Les systèmes d'aide à la conduite sont de plus en plus présents dans nos véhicules et nous garantissent un meilleur confort et plus de sécurité. Dans cette thèse, nous nous sommes particulièrement intéressés aux systèmes d'adaptation automatique de la vitesse limite. Nous avons proposé une approche alliant vision et navigation pour gérer de façon optimale l'environnement routier.Panneaux, panonceaux et marquages sont autant d'informations visuelles utiles au conducteur pour connaître les limitations temporaires en vigueur sur la route. La reconnaissance des premiers ont fait l'objet ces dernières années d'un grand nombre d'études et sont même commercialisés, contrairement aux seconds. Nous avons donc proposé un module de détection et classification de panonceaux sur des images à niveaux de gris. Un algorithme de reconstruction morphologique associé à une croissance de régions nous ont permis de concentrer la segmentation sur les zones fortement contrastées de l'image entourées d'un ensemble de pixels d'intensité similaire. Les rectangles ainsi détectés ont ensuite fait l'objet d'une classification au moyen de descripteurs globaux de type PHOG et d'une structure hiérarchique de SVMs. Afin d'éliminer en dernier lieu les panonceaux ne s'appliquant pas à la voie sur laquelle circule le véhicule, nous avons pris en compte les informations de marquages à l'aide d'une machine d'états.Après avoir élaboré un module de vision intégrant au mieux toutes les informations disponibles, nous avons amélioré le système de navigation. Son objectif est d'extraire d'une base de données embarquée, le contexte de conduite lié à la position du véhicule. Ville ou non, classe fonctionnelle et type de la route, vitesse limite sont extraits et modélisés sous forme d'attributs. La fiabilité du capteur est ensuite calculée en fonction du nombre de satellites visibles et de la qualité de numérisation du réseau. La confiance en chaque vitesse limite sera alors fonction de ces deux ensembles.La fusion des deux sources au moyen de Demspter-Shafer a conduit à de très bonnes performances sur nos bases de données et démontré l'intérêt de tous ces éléments. / ADAS (Autonomous Driving Assistance Systems) are more and more integrated in vehicles and provide to drivers more confort and safety. In this thesis, we focused on Intelligent Speed Adaptation. We proposed an approach combining vision and navigation in order to optimally manage the driving context information.Roadsigns, subsigns and markings are visual data used by the driver to determine the current temporary speed limitations. Many research were conducted during last years to recognise the first one, contrary to the second. Commercialised products are even implemented in vehicles. We thus developped a subsign detection and classification module using greyscale images. A morphological reconstruction with a growing region helped us to focus the segmentation on highly contrasted pixels surrounded by homogeneous regions. Global descriptors such as PHOGs combined to a hierarchical structure of SVMs were then used to classify the output rectangles. Finally, we eliminated subsigns which are not applicable to the current lane by considering markings.After having developed a vision module integrating all the available information, we improved the navigation system. The objective was to extract from an embedded database the driving context related to the vehicle position. Urban context or not, functional class, road type and speed limit were collected and modelised into criteria. The sensor reliability was then computed and depended on the satellite configuration and the network digitisation quality. Confidence in each speed limit combined all these elements.Fusion of both sources with the Dempster-Shafer theory led to very good performances on our databases et showed the importance of all the used information.

Les drones ou systèmes de drones aériens jouent un rôle de plus en plus important danstous les domaines, spécialement les drones à décollage et atterrissage verticaux. L’un desplus connus est le Quadrotor et, sans doute, il est la plateforme de recherche la plus utilisée.Cette thèse traite le problème de l’estimation et de la commande d’attitude appliqué àun corps rigide se déplaçant dans l’espace 3D tel que le Quadrotor. La première contributionde cette thèse est la conception et l’implémentation d’une solution d’estimation d’attitude.Celle-ci est basée sur un ensemble de filtres complémentaires combinés avec un algorithmealgébrique tel que TRIAD, QUEST, etc. avec la possibilité de choisir deux formes différentesdes filtres: la première dénommée forme Directe, et la seconde dénommée forme Passive.Les filtres proposés ont une flexibilité dans le choix de l’ordre qui peut être pris grand afinde bien réduire l’effet du bruit de mesure et permettent d’aboutir à un estimateur qui peutprendre en compte le biais éventuel des gyromètres. L’analyse par la théorie de Lyapunovprouve que les erreurs d’estimation tendent globalement et asymptotiquement vers zéro. Unesuite logique de cette première contribution est la proposition d’une solution pour la commanded’attitude qui constitue la deuxième contribution de cette thèse. Elle se traduit par ledéveloppement d’une nouvelle loi de commande d’attitude d’un corps rigide dans l’espace3D, dans laquelle seulement les vecteurs de mesures inertiels avec les mesures des gyromètressont utilisés. Elle utilise le principe de fusion des données à travers un filtre complémentairepermettant l’élimination des bruits des mesures tout en assurant une stabilité presque globalede l’équilibre désiré. La troisième contribution est une loi de commande pour la stabilisationd’attitude sans mesure de vitesse angulaire, ni mesure d’attitude. Pour cela, un systèmelinéaire auxiliaire basé sur les mesures des vecteurs inertiels a été introduit. Ce dernier sesubstitue au manque de l’information de la vitesse angulaire. L’analyse de stabilité du contrôleurproposé est basée sur la théorie de Lyapunov couplée avec le théorème de LaSalle. Ellepermet de conclure sur la stabilité presque globale de l’équilibre désiré. Les performances dessolutions proposées ont été validées par un ensemble de tests expérimentaux / Nowadays, we see a growing popularity of the use of Unmanned Aerial Vehicles (UAV) ofespecially Vertical Take-Off and Landing (VTOL) type. One of the most known VTOL is thequadrotor or Quadcopter which is probably the most used one as a research platform. Thisthesis deal with attitude control and estimation techniques applied to a rigid body movingin 3D space such as Quadcopter VTOL. The first contribution of this thesis is the design ofa new class of complementary linear-like filters allowing the fusion of inertial vector measurementswith angular velocity measurements and combined with algebraic algorithms asTRIAD, QUEST etc. to give an efficient attitude estimation solution. This class of filtersallows several possibilities of implementation such as the order of the filters which can bechosen high in order to reduce more the measurement noise and the form of the filters thatcan be direct or passive and the ability to take into account the possible gyro bias. Lyapunovanalysis shows the global asymptotic convergence of the estimation errors to zero. The sameprinciple of data fusion is used for the proposed new attitude control law in which the complementaryfilters were included to reduce the effect of measurement noise. The obtainedcontroller ensures almost global stability of the desired equilibrium point; it represents thesecond contribution of this thesis. The third contribution takes into consideration an interestingspecial case, where instantaneous measurements of attitude and angular velocity areunavailable. A first order linear auxiliary system based directly on vector measurements isused in an observer-like system to handle the luck of angular velocity. The proposed controllerensures almost global asymptotic stability of the trajectories to the desired equilibriumpoint. Detailed sets of experiments were done to validate the obtained results

Master of Science / Department of Electrical and Computer Engineering / Christopher L. Lewis / This thesis presents a method to perform universal object segmentation on fused SICK laser range data and color CCD camera images collected from a mobile robot. This thesis also details the method of fusion. Fused data allows for higher resolution than range-only data and provides more information than color-only data. The segmentation method utilizes the Expectation Maximization (EM) algorithm to detect the location and number of universal objects modeled by a six-dimensional Gaussian distribution. This is achieved by continuously subdividing objects previously identified by EM. After several iterations, objects with similar traits are merged. The universal object model performs well in environments consisting of both man-made (walls, furniture, pavement) and natural objects (trees, bushes, grass). This makes it ideal for use in both indoor and outdoor environments. The algorithm does not require the number of objects to be known prior to calculation nor does it require a training set of data. Once the universal objects have been segmented, they can be processed and classified or left alone and used inside robotic navigation algorithms like SLAM.

京都大学 / 新制・課程博士 / 博士(工学) / 甲第23178号 / 工博第4822号 / 新制||工||1753(附属図書館) / 京都大学大学院工学研究科都市社会工学専攻 / (主査)教授 山田 忠史, 教授 藤井 聡, 准教授 SCHMOECKER Jan-Dirk / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DFAM

Ziel dieser Arbeit ist es, robuste und performante Algorithmen für die Fusion von polizeilichen Unfalldaten zur Testszenariengenerierung im Rahmen der Absicherung automatisierter Fahrfunktionen zu generieren. In dieser Arbeit werden dabei Methoden zur Datenfusion in Kombination mit generativen und Klassifikationsmodellen untersucht. Eine spezifische Variable vom Empfänger wird während des Datenfusionsverfahrens im Voraus entfernt. Ein Spender mit den gemeinsamen Variablen wird verwendet, um die Vorhersage für die fehlende spezifische Variable im Empfänger zu erhalten. Als Methode werden Ensembles aus Distance-Hot-Deck und Machine-Learning Verfahren für die Vorhersage verwendet. Nach der Vorhersage werden die Ergebnisse anhand ausgewählter Bewertungsmetriken bewertet. Darüber hinaus werden zwei generative Modelle eingeführt, um Datensätze unterschiedlicher Qualität zu synthetisieren. Ziel ist es, die Robustheit der Ensembles mit den synthetisierten „Rauschdaten“ zu testen und die Performance von Ensembles mit den synthetisierten Daten hoher Qualität zu verbessern. Schließlich können Erkenntnisse darüber gewonnen werden, welche Ensembles die besten Ergebnisse für die Datenfusion liefern.:1. Einleitung 2. Grundlagen 3. Randbedingungen 4. Vorgehensweise 5. Ergebnisse 6. Diskussion & Ausblick