A simetria facial foi investigada como fator de atratividade em quatro experimentos. Fotos frontais em preto e branco de faces de homens e mulheres foram manipuladas por computação gráfica para gerar faces simétricas. No Exp. I as faces simétricas foram geradas a partir da reflexão das metades laterais, direita e esquerda, de cada face. Essas faces simétricas e suas respectivas faces naturais foram apresentadas a sujeitos para julgar o quão atrativa elas eram. Os resultados mostraram que faces assimétricas (naturais) foram julgadas como mais atrativas que as simétricas. No Exp. II utilizaram-se as mesmas faces simétricas e naturais do Exp. I, porém, excluindo-se os elementos externos da face por meio de uma moldura elíptica. Essas faces foram apresentadas aos pares e pediu-se para os participantes escolher a mais atrativa, além de julgar seu grau de atratividade. Os resultados mostraram que nenhuma foto simétrica foi julgada como mais atrativa que sua respectiva face natural, bem como as faces naturais foram mais escolhidas que as simétricas. A exclusão dos elementos externos das faces não contribuiu para aumentar o grau de atratividade das mesmas. No Exp. III as faces simétricas foram geradas por técnica de morphing a partir da imagem da face original e a sua respectiva imagem refletida. A apresentação e julgamentos das faces seguiram o modelo do Exp. II. Os resultados mostraram que nenhuma face simétrica obteve escore de atratividade maior que as naturais, mas com relação às escolhas, para faces masculinas houve maior número de escolhas para as faces simétricas. No Exp. IV foram utilizadas as mesmas faces simétricas e naturais do Exp. III, excluindo-se os elementos faciais externos. Os resultados indicaram maior escores de atratividade, bem como um maior número de escolhas das faces simétricas. Comparadas ao Exp. III houve um aumento nos escores de atratividade para as faces simétricas e uma diminuição dos escores para as faces naturais. Conclui-se que a simetria não deve ser considerada como um fator isolado na análise da atratividade facial; relações entre outros elementos podem contribuir para tornar uma face mais atrativa. / The facial symmetry was investigated as attractiveness factor in four experiments. Front pictures in black and white of men\'s and women?s faces were manipulated by graphic computation to create symmetrical faces. In Exp. I, the symmetrical faces were created starting from the lateral half right and left reflection, of each face. Those symmetrical faces and their respective natural faces were presented to people that had to judge how attractive they were. The results showed that asymmetrical faces (natural) were judged as more attractive than the symmetrical ones. In Exp. II, we used the same symmetrical and natural faces of Exp. I, however, being excluded face?s external elements through an elliptic frame. These faces were presented in pairs and we asked for the participants to choose the most attractive, besides judging the attractiveness degree. The results showed that no symmetrical picture was judged as more attractive than its respective natural face, as well as the natural faces were more chosen than the symmetrical ones. The exclusion of the external elements of the faces didn\'t contribute to increase the attractiveness degree of themselves. In Exp. III, the symmetrical faces were created by morphing technique starting from the original face image and its respective reflected image. The presentation and judgments of the faces followed the model of Exp. II. The results showed that no symmetrical face obtained score of larger attractiveness than the natural ones, but regarding the choices, for masculine faces there was larger number of choices for the symmetrical faces. In Exp. IV we used the same symmetrical and natural faces of Exp. III, being excluded the external facial elements. The results indicated larger attractiveness scores, as well as a larger number of choices fore the symmetrical faces. Comparing Exp. IV with Exp. III, we had an increase in the attractiveness scores for the symmetrical faces and a decrease of the scores for the natural faces. We concluded that the symmetry should not be considered as an isolated factor in the facial attractiveness analysis; the relationships among other elements can contribute to turn a more attractive face.

Este trabalho tem como objetivo desenvolver uma metodologia baseada em lógica nebulosa, (KLIR ; YUAN, 1995) para detectar faces humanas em imagens digitais. Considerando que pessoas conseguem reconhecer facilmente as faces humanas, este trabalho prevê a pesquisa da informação relativa a esse reconhecimento utilizando os resultados obtidos, em um esquema \"fuzzy\", para identificação de faces humanas em imagens digitais. É proposto então um algoritmo que classifique automaticamente as regiões de uma imagem em faces humanas ou não. O conhecimento para a construção da base de regras foi obtido através de informações das pessoas por meio de uma pesquisa de campo onde as respostas foram numericamente armazenadas para a geração da classificação nebulosa. Foram gerados desenhos line-draw que de uma maneira global representam as faces humanas. Esses desenhos foram apresentados às pessoas entrevistadas que forneceram subsídios para a montagem das regras \"fuzzy\". O algoritmo foi capaz de a partir daí, identificar faces humanas em imagens digitalizadas. Imagens simples contendo uma face frontal foram submetidas a um algoritmo e ao passarem por processamento (extração de bordas, erosão, binarização, etc...) perderam características, tornando difícil sua identificação. O algoritmo \"fuzzy\" foi capaz de atribuir um grau de pertinência à imagem dentro do conjunto de faces humanas frontais. A lógica nebulosa possui história recente, porém, desde cedo, demonstra sua versatilidade, principalmente por traduzir modelos não lineares ou imprecisos, os quais não apresentam convergência através de modelagem matemática convencional. / The present master dissertation aims to develop a methodology based on fuzzy pattern (KLIR; YUAN, 1995) to detect human faces in digital images. Considering that people are easily able to recognize human faces, this study foresees the research of the relative information to this recognition using the acquire results, in a \"fuzzy\" scheme, for the identification of human faces in digital images. It\'s proposed an algorithm which automatically classifies or not the regions of an image in human faces. It is based on the information acquired from people by means of a field research where the answers are stored numerically for the creation of the fuzzy classification. Drawings line-draw were created to represent human faces and were presented to the people interviewed to furnish information for the creation of the fuzzy rules. After that the algorithm was able to identify human faces in digitalized images. The algorithm utilizes simple images containing a frontal face, which lose their characteristics when they are processed (edges extration, erosion, binary image, etc...) and make their identification difficult. The fuzzy algorithm is also able to classify the images within the set of frontal human faces. The fuzzy logic has a recent history, however, it has always demonstrated its versatility, mainly regarding the translation of non-linear or inexact models which do not present conventional mathematical convergence through modeling.

Social anxiety disorder has several impairments (including attention bias in ratings of facial expressions). Character strengths has been seen to increase well-being and functioning among healthy individuals. With this in mind, three aims were stated; Is there a relation between SAD and VIA, can this relation be explained by confounding’s and does ratings of faces tell anything about the relation? Data were collected through a survey from 41 participants (13 men) with a mean age of 30 years. Correlation and regression models were performed to see if these constructs were related. The findings showed that character strengths and social anxiety were correlated, and that the regression model did not predict SAD. The regression model for Via were significant with all confounding variables. Ratings of facial expression were not related to any variables. Further studies need to look more into this correlation to see the underpinnings of these constructs.

The thesis is concerned with an in-depth analysis and evaluation of the JBoss RichFaces component framework with regards to its particular strengths and weaknesses. The framework is examined both from the theoretical and practical point of view and also subjected to comparative analysis with other similar products on the market. Apart from the theoretical background and profound subject explanation, the practical part of the thesis offers a full-fledged referential application with fragments of commented code and thorough exploration of the framework's professional usage.

O Reconhecimento de faces consiste em, a partir de uma imagem, identificar ou verificar um ou mais indivíduos através de um banco de dados de faces. O reconhecimento de faces é uma tarefa de grande interesse, principalmente pelo grande número de possíveis aplicações. Dessa forma, existem diversos métodos para lidar com o problema. No entanto, apesar da maioria dos métodos conseguirem bons resultados em ambientes controlados, quando há variações de iluminação, pose ou expressão facial, esse desempenho é reduzido. Buscando lidar com as dificuldades existentes, este trabalho propõe um método para o reconhecimento de faces utilizando os conjuntos-K. Os conjuntos-K são modelos conexionistas baseados em populações de neurônios, concebidos através de estudos e análises do sistema olfativo animal. Estes modelos apresentam estrutura e comportamento biologicamente mais plausíveis que os modelos tradicionais de redes neurais. Os conjuntos-K vêm sendo usados em diversas tarefas de aprendizado de máquina, apresentando bons resultados principalmente na resolução de problemas complexos ou com ruídos. Devido ao grande potencial dos conjuntos-K para reconhecimento de padrões em ambientes complexos e ruidosos, é levantada a hipótese de que um método baseado nos conjuntos-K alcance um melhor desempenho que os métodos existentes na literatura. O método proposto foi avaliado utilizando dois bancos de dados, AT&T e Yale B, o primeiro com pequenas variações em relação a pose e expressão facial e o segundo com grandes variações de iluminação fornecendo um cenário mais complexo. Os resultados mostraram que o método proposto consegue um desempenho equivalente ou um pouco inferior que os outros métodos avaliados para o primeiro banco de dados. Porém, para o segundo banco de dados, que fornece o cenário mais complexo, o método proposto supera os demais métodos. / Face recognition consists of, from a picture, identifying or checking one or more individuals through a face database. Face recognition is an interesting task mainly because of the large number of possible applications. This way, there are various methods to deal with the problem. However, although most methods achieve good results in controlled environments, when there are lighting, pose or facial expression variations, this performance is reduced. Seeking to deal with the existing difficulties, this work proposes a method for recognizing faces using K-sets. The K-sets are connectionist models based on neuron populations, designed from studies and analyses of the animal olfactory system. These models present more biologically plausible structure and behavior than traditional neural network models. K-sets have been used in various machine learning tasks with good results, mainly in the resolution of complex or noisy problems. Due to the great potential of K-sets for pattern recognition in complex and noisy environments, a hypothesis is raised that a method based on K-sets achieves a better performance than existing methods. The proposed method was evaluated using two databases, AT&T and Yale B, the first with small variations of pose and facial expressions and the second with large variations in illumination providing a more complex scenario. The results show that the proposed method achieve an equivalent or slightly lower performance than the other methods evaluated for the first database. However, for the second database, which provides the more complex scenario, the proposed method outperforms the other methods.

[pt] Identificar um indivíduo a partir de uma imagem de face é uma tarefa simples para seres humanos e extremamente difícil para a Visão Computacional. Esta questão tem motivado diversos grupos de pesquisa em todo o mundo, especialmente a partir de 1993. Inúmeros trabalhos realizados até o momento encaram uma imagem digital de n pixels como um vetor num espaço n-dimensional, onde n é em geral muito grande. Imagens de rostos humanos possuem, contudo, grande redundância: todas contém dois olhos, um nariz, uma boca, e etc. É possível, portanto, trabalhar em uma base deste espaço em que faces possam ser adequadamente caracterizadas a partir de um conjunto de p componentes, onde p é muito menor quen. É com este enfoque que o presente trabalho estuda sistemas de reconhecimento de faces que consistem de um estágio de redução de dimensionalidade, realizado pela técnica de Análise de Componentes Principais (PCA), seguido de um modelo classificador. No estágio da PCA, as imagens de n pixels são transformadas em vetores de p características a partir de um conjunto de treinamento. Três classificadores conhecidos na literatura são estudados: os classificadores de distância (EUclideana e de Mahalanobis), a rede neural de Funções Base Radiais (RBF), e o classificador de Fisher. Este trabalho propõe, ainda, um novo classificador que introduz o conceito de Matrizes de Covariança Misturadas (MPM) no classificador gaussiano de Máxima Probabilidade. Os quatros classificadores são avaliados através da variação de seus respectivos parâmetros e utilizam como imagens o banco de faces da Olivetti. Nos experimentos realizados para comparar tais abordagens, o novo classificador proposto atingiu as maiores taxas de reconhecimento e apresentou menorsensibilidade à escolha do conjunto de faces de treinamento. / [en] Identifying an individual based on a face image is a simple task for humans to perform and a very difficult one for Vision Computing. Since 1993, several research groups in all over the world have been studied this problem. Most of the methods proposed for recognizing the identity of an individual represent a n intensity pixel image as a n- dimensional vector, when, in general, n is a very large number value. Face images are highly redundant, since every individual has two eyes, one nose, one mouth and so on. Then, instead of using n intensity values, it is generally possible to characterize an image instance by a set of p features, for p < < n. This work studies face recognition systems consisting of a PCA stage for dimensionality reduction followed by a classifier. The PCA stage takes the n-pixels face images and produces the corresponding p most expensive features, based on the whole available training set. Three classifiers proposed in the literature are studied: the Euclidean and Mahalanobis distances, the RBF neural network, and the Fisher classifier. This work also proposes a new classifier, which introduces the concept of Mixture Covariance Matrices (MPM) in the Minimum Total Probality of Misclassification rule for normal populations. The four classifiers are evaluated using the Olivetti Face Database varying their parameters in a wide range. In the experiments carried out to compare those approaches the new proposed classifier reached the best recognition rates and showed to be less sensitive to the choice of the training set.

Notre objectif est ici d’apporter des éléments de réflexion, à partir du corpus psychanalytique concernant les effets de l’exposition précoce aux écrans sur la croissance psychique. Ce travail se centre sur le développement du bébé et du jeune enfant en proposant une analyse des effets de cette invasion numérique dans la construction psychique et l’instauration des premiers liens. Nous avons souhaité construire cette problématique en abordant en premier lieu les fondements de la vie psychique ; ceci afin de poser un cadre théorique de réflexion et de mieux questionner, dans un second temps, l’impact des écrans sur les interactions précoces et la construction subjective de l’enfant. La situation du bébé, à l’aube de son existence, s’inscrit d’emblée du côté des échanges avec son entourage, au sein d’un environnement singulier. C’est à partir de cette rencontre, de la qualité des interactions précoces et de la capacité de l’entourage d’adapter l’environnement à ses besoins, que va dépendre la réussite de son individuation future. À travers nos lectures, l’importance de l’ancrage corporel et relationnel nous est apparu déterminant dans le déploiement de la vie psychique. Le jeu nous a semblé être le socle de cet ancrage corporel et relationnel. Nous avons dès lors pensé nécessaire qu’il y ait du jeu pour que le je advienne ; ou, en d’autres termes, que le partage ludique, au sein des interactions précoces, constitue un élément déterminant dans la construction subjective. Le Jeu des trois figures, outil de prévention à l’adresse des enfants, a été le support de notre recherche clinique. Il offre un lieu de verbalisation autour des nombreuses images matérielles qui inondent le quotidien des enfants. Il permet de partir de leurs éprouvés corporels, issus de l’exposition aux écrans, afin de soutenir un travail de symbolisation ; symbolisation multiple : imagée, en favorisant leurs capacités représentatives, verbale, en permettant la construction narrative d’une histoire, et sensori-motrice, en mobilisant le corps à travers le repérage des mimiques et le « jeu de faire semblant ». C’est au croisement de ces trois dimensions - la construction narrative, l’engagement corporel et la capacité de faire semblant - qu’un travail de symbolisation peut s’engager pour l’enfant. Les résultats de cette recherche démontrent que le J3F, adapté au cadre thérapeutique, est un outil pertinent pour relancer les processus de symbolisation. / Our objective is to provide elements for reflection, based on the psychoanalytic corpus concerning the effects of early exposure to screens on psychic growth. This work focuses on the development of the baby and the young child by offering an analysis of the effects of this digital invasion in the psychological construction and the establishment of attachment. We wanted to approach this issue by firstly addressing the foundations of a child's psyche ; this in order to establish a theoretical framework for reflection and subsequently to better question the impact of screens on early interactions and the subjective construction of the child. From the very beginning a baby is influenced by interactions with its entourage,with in a singular environment. It is on the basic of the seen counters, the quality of its early interactions and the ability of the entourage to adapt the environment to the baby's needs, that the success of the baby's future individualisation will depend. Through our readings, the importance of physical and relational anchoring, appeared to us to be central to the deployment of the psyche. Play seemed to us to be the foundation of this physical and relational anchoring.
We therefore thought it necessary for there to be play for the "I" to happen; or, in other words, that playful sharing as part of early interactions, constitutes a determining element in subjective construction. The “three faces” game, a prevention tool for children, has been the support of our clinical research. It offers a place for verbalisation around the many material images that flood the daily lives of children. It makes it possible to start from their physical experience caused by exposure to the screens and move towards a work of symbolisation. Multiple symbolisation such as: pictorial symbolisation ie by encouraging their representative capacity; verbal symbolisation ie by allowing the narrative construction of a story, and sensory motor symbolisation, ie by mobilising the body through the identification of mimics and the "game of pretending". It is at the intersection of these three dimensions-narrative construction, physical engagement and the ability to pretend - that a symbolic work can be engaged for the child. The results of this research show that J3F, adapted to the therapeutic framework, is a relevant tool for relaunching symbolisation processes

Growing regions and tighter zoning in urban areas are pushing the hydrological bal-ances to establish new equilibriums which are causing a stress on the groundwater. Urbanization can affect the groundwater in several ways in which both raising and lowering of groundwater tables are a possibility. Both ways, sudden changes may bring on socioeconomic costs for the unprepared. Hydrogeological modelling creates the possibilities to visualise processes that cannot be seen with the naked eye. By combin-ing knowledge about the studied area from tests and measurements a conceptual model and additionally a numerical model can be created. To study the magnitude groundwater sensitivity to changes in land-cover a hydrogeological model was created using COMSOL multiphysics within the frame of a case study concerning a horse racetrack located in Täby, north of Stockholm. The model was calibrated against known data and was the applied on a future scenario where both the land-use and climate were changed. The outcome of the model showed that hydrogeological mod-elling is sensitive to the amount and quality of the in-data. Several insecurities in the results can be traced back to a lack of base material and by changing one parameter the result of other calibrated parameters would also change. Equifinality could thus be established to be a major issue when performing groundwater modelling. Further studies of relevant data requirements for different model objectives are required.

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付記する学位プログラム名: 霊長類学・ワイルドライフサイエンス・リーディング大学院 / 京都大学 / 0048 / 新制・課程博士 / 博士(理学) / 甲第22034号 / 理博第4538号 / 新制||理||1652(附属図書館) / 京都大学大学院理学研究科生物科学専攻 / (主査)教授 友永 雅己, 准教授 宮地 重弘, 教授 濱田 穣 / 学位規則第4条第1項該当 / Doctor of Science / Kyoto University / DFAM