Orientador: Jorge Stolfi / Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Computação / Made available in DSpace on 2018-08-16T21:27:57Z (GMT). No. of bitstreams: 1 Zampieri_CarlosEliasArminio_M.pdf: 4003666 bytes, checksum: a730c8935e9f68bc9c1cd9a6e9d68c8c (MD5) Previous issue date: 2010 / Resumo: Neste trabalho apresentamos um método geral para busca de imagem por conteúdo (BIPC, CBIR) em grandes coleções de imagens, usando estimação intervalar multiescala de distância. Consideramos especificamente buscas por exemplo, em que o objetivo é encontrar a imagem da coleção que é mais próxima a uma imagem dada, segundo alguma função de distância de imagens. Neste trabalho não procuramos desenvolver métricas que melhor atendem as intenções do usuário; em vez disso, supondo que a métrica está escolhida, apresentamos um algoritmo genérico (que denominamos MuSIS, de Multiscale Image Search) para realizar a busca de maneira eficiente usando aritmética intervalar. Estimativas intervalares das distâncias entre imagens são usadas para eliminar rapidamente imagens candidatas, considerando apenas versões reduzidas das mesmas, de maneira semelhante ao paradigma de otimização branch-and-bound. Como parte deste trabalho, desenvolvemos estimadores intervalares eficazes para distância euclidiana e algumas variantes da mesma, incluindo métricas sensíveis ao gradiente em escalas variadas. Experimentos indicaram que o método promove significativa redução de custos em relação à busca exaustiva. Apesar de menos eficiente do que outros métodos comumente usados para BIPC, o algoritmo MuSIS sempre retorna a resposta exata - isto é, a imagem mais próxima na métrica escolhida - e não apenas uma aproximação. A abordagem MuSIS é compatível com uma ampla variedade de funções de distância, sem a necessidade de pré-calcular ou armazenar descritores específicos para cada função / Abstract: We present a general method for content-based image retrieval (CBIR) in large image collections, using multiscale interval distance estimation. We consider specifically queries by example, where the goal is to find the image in the collection that is closest to a given image, according to some image distance function. In this work we do not aim to develop metrics that best meet the user's intentions; instead, assuming that the metric is chosen, we describe an algorithm (wich we call MuSIS, for MultiScale Image Search) to perform the search efficiently using interval arithmetic. Interval estimates of the image distances are used to quickly discard candidate images after examining only small versions of them, in a manner similar to the branch-and-bound optimization paradigm. As part of this work, we developed effective interval estimators for the Euclidean distance and for some variations of it, including metrics that are sensitive to the gradient at various scales. Experiments indicate that the method yields significant cost savings over exhaustive search. Although less efficient than other methods commonly used for CBIR, the MuSIS algorithm always returns the exact answer - that is, the nearest image in metric chosen - and not just an approximation thereof. The MuSIS approach is compatible with a wide variety of distance functions without the need to pre-compute or store specific descriptors for each function / Mestrado / Processamento de Imagens / Mestre em Ciência da Computação

L'imagerie par résonance magnétique fonctionnelle (IRMf) étant une technique non invasive pour l'étude de cerveau, elle a été employée pour comprendre les mécanismes cérébraux sous-jacents à la prise alimentaire. Cependant, l'utilisation de stimuli liquides pour simuler la prise alimentaire engendre des difficultés supplémentaires par rapport aux stimulations visuellement habituellement mises en œuvre en IRMf. L'objectif de cette thèse a donc été de proposer une méthode robuste d'analyse des données tenant compte de la spécificité d'une stimulation alimentaire. Pour prendre en compte le mouvement dû à la déglutition, nous proposons une méthode de censure fondée uniquement sur le signal mesuré. Nous avons de plus perfectionné l'étape de normalisation des données afin de réduire la perte de signal. La principale contribution de cette thèse est d'implémenter l'algorithme de Ward de sorte que parcelliser l'ensemble du cerveau soit réalisable en quelques heures et sans avoir à réduire les données au préalable. Comme le calcul de la distance euclidienne entre toutes les paires de signaux des voxels représente une part importante de l'algorithme de Ward, nous proposons un algorithme cache-aware du calcul de la distance ainsi que trois parallélisations sur les architectures suivantes : architecture à mémoire partagée, architecture à mémoire distribuée et GPU NVIDIA. Une fois l'algorithme de Ward exécuté, il est possible d'explorer toutes les échelles de parcellisation. Nous considérons plusieurs critères pour évaluer la qualité de la parcellisation à une échelle donnée. À une échelle donnée, nous proposons soit de calculer des cartes de connectivités entre les parcelles, soit d'identifier les parcelles répondant à la stimulation à l'aide du coefficient de corrélation de Pearson. / As a non-invasive technology for studying brain imaging, functional magnetic resonance imaging (fMRI) has been employed to understand the brain underlying mechanisms of food intake. Using liquid stimuli to fake food intake adds difficulties which are not present in fMRI studies with visual stimuli. This PhD thesis aims to propose a robust method to analyse food stimulated fMRI data. To correct the data from swallowing movements, we have proposed to censure the data uniquely from the measured signal. We have also improved the normalization step of data between subjects to reduce signal loss.The main contribution of this thesis is the implementation of Ward's algorithm without data reduction. Thus, clustering the whole brain in several hours is now feasible. Because Euclidean distance computation is the main part of Ward algorithm, we have developed a cache-aware algorithm to compute the distance between each pair of voxels. Then, we have parallelized this algorithm for three architectures: shared-memory architecture, distributed memory architecture and NVIDIA GPGPU. Once Ward's algorithm has been applied, it is possible to explore multi-scale clustering of data. Several criteria are considered in order to evaluate the quality of clusters. For a given number of clusters, we have proposed to compute connectivity maps between clusters or to compute Pearson correlation coefficient to identify brain regions activated by the stimulation.

Masters of Science / The multivariate two-sample tests provide a means to test the match between two multivariate distributions. Although many tests exist in the literature, relatively little is known about the relative power of these procedures. The studies reported in the thesis contrasts the effectiveness, in terms of power, of seven such tests with a Monte Carlo study. The relative power of the tests was investigated against location, scale, and correlation alternatives. Samples were drawn from bivariate exponential, normal and uniform populations. Results from the power studies show that there is no single test which is the most powerful in all situations. The use of particular test statistics is recommended for specific alternatives. A possible supplementary non-parametric graphical procedure, such as the Depth-Depth plot, can be recommended for diagnosing possible differences between the multivariate samples, if the null hypothesis is rejected. As an example of the utility of the procedures for real data, the multivariate two-sample tests were applied to photometric data of twenty galactic globular clusters. The results from the analyses support the recommendations associated with specific test statistics.

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<p>Recent advances in technology have allowed researchers to collect high-dimensional biological data simultaneously. In genomic studies, for instance, measurements from tens of thousands of genes are taken from individuals across several experimental groups. In time course microarray experiments, gene expression is measured at several time points for each individual across the whole genome resulting in massive amount of data. In such experiments, researchers are faced with two types of high-dimensionality. The first is global high-dimensionality, which is common to all genomic experiments. The global high-dimensionality arises because inference is being done on tens of thousands of genes resulting in multiplicity. This challenge is often dealt with statistical methods for multiple comparison, such as the Bonferroni correction or false discovery rate (FDR). We refer to the second type of high-dimensionality as gene specific high-dimensionality, which arises in time course microarry experiments due to the fact that, in such experiments, sample size is often smaller than the number of time points ($n</p> <p>In this thesis, we use the growth curve model (GCM), which is a generalized multivariate analysis of variance (GMANOVA) model, and propose a moderated test statistic for testing a special case of the general linear hypothesis, which is specially useful for identifying genes that are expressed. We use the trace test for the GCM and modify it so that it can be used in high-dimensional situations. We consider two types of moderation: the Moore-Penrose generalized inverse and Stein's shrinkage estimator of $ S $. We performed extensive simulations to show performance of the moderated test, and compared the results with original trace test. We calculated empirical level and power of the test under many scenarios. Although the focus is on hypothesis testing, we also provided moderated maximum likelihood estimator for the parameter matrix and assessed its performance by investigating bias and mean squared error of the estimator and compared the results with those of the maximum likelihood estimators. Since the parameters are matrices, we consider distance measures in both power and level comparisons as well as when investigating bias and mean squared error. We also illustrated our approach using time course microarray data taken from a study on Lung Cancer. We were able to filter out 1053 genes as non-noise genes from a pool of 22,277 genes which is approximately 5\% of the total number of genes. This is in sync with results from most biological experiments where around 5\% genes are found to be differentially expressed.</p> / Master of Science (MSc)

Cette étude porte sur la distance parcourue pour commettre un crime à Gatineau en 2006. Peu d’études canadiennes récentes ont porté sur le sujet. De plus, il existe un vide de connaissances sur la mobilité des délinquants dans les petites villes et les banlieues. La présente recherche vise à comparer trois mesures de distance différentes, à vérifier si la distance parcourue varie en fonction du type de crime et à voir si les variables de temps (jour de la semaine, moment de la journée et saison) de même que certaines caractéristiques des suspects (âge, sexe et lieu de résidence) ont un impact sur la distance parcourue. Pour chaque crime, l’adresse du suspect et le lieu du crime ont été géocodées pour ensuite calculer la distance entre les deux points. Il ressort de l’analyse de la forme des courbes de distances que seules les agressions sexuelles présentent une zone tampon. Les résultats des analyses statistiques indiquent que les jeunes sont plus mobiles que les suspects plus âgés et que les hommes parcourent une distance plus élevée que les femmes. Étonnement, la distance parcourue ne diffère pas significativement selon la saison et le moment de la journée. Enfin, comparativement aux autres criminels, les délinquants qui ont commis un vol qualifié sont ceux qui ont parcouru les plus grandes distances. / This study focuses on the journey to crime of the offenders who have committed a crime in Gatineau in 2006. There are only a few recent Canadian studies on the subject. In addition there is a vacuum of knowledge on the journey to crime in smaller cities and suburbs. This research is designed to compare three different measures of distance, to check if the distance varies depending on the type of crime and see if the variables of time (day of week, time of day and season) as well as some characteristics of suspects (age, sex and place of residence) have an impact on the distance traveled. For each crime, the address of the suspect and the crime location were geocoded then, the distance between the two points was calculated. An analysis of the shapes curves pattern of the distances indicates that sexual assault is the only type of crime which possesses a buffer zone. The results of statistical analysis show that young people are more mobile than older suspects and that men travel a greater distance than women. Surprisingly, the distance does not differ significantly according to season and time of day. Finally, compared to the other criminal offenders, those who have committed a robbery traveled the greatest distances.

Cette étude porte sur la distance parcourue pour commettre un crime à Gatineau en 2006. Peu d’études canadiennes récentes ont porté sur le sujet. De plus, il existe un vide de connaissances sur la mobilité des délinquants dans les petites villes et les banlieues. La présente recherche vise à comparer trois mesures de distance différentes, à vérifier si la distance parcourue varie en fonction du type de crime et à voir si les variables de temps (jour de la semaine, moment de la journée et saison) de même que certaines caractéristiques des suspects (âge, sexe et lieu de résidence) ont un impact sur la distance parcourue. Pour chaque crime, l’adresse du suspect et le lieu du crime ont été géocodées pour ensuite calculer la distance entre les deux points. Il ressort de l’analyse de la forme des courbes de distances que seules les agressions sexuelles présentent une zone tampon. Les résultats des analyses statistiques indiquent que les jeunes sont plus mobiles que les suspects plus âgés et que les hommes parcourent une distance plus élevée que les femmes. Étonnement, la distance parcourue ne diffère pas significativement selon la saison et le moment de la journée. Enfin, comparativement aux autres criminels, les délinquants qui ont commis un vol qualifié sont ceux qui ont parcouru les plus grandes distances. / This study focuses on the journey to crime of the offenders who have committed a crime in Gatineau in 2006. There are only a few recent Canadian studies on the subject. In addition there is a vacuum of knowledge on the journey to crime in smaller cities and suburbs. This research is designed to compare three different measures of distance, to check if the distance varies depending on the type of crime and see if the variables of time (day of week, time of day and season) as well as some characteristics of suspects (age, sex and place of residence) have an impact on the distance traveled. For each crime, the address of the suspect and the crime location were geocoded then, the distance between the two points was calculated. An analysis of the shapes curves pattern of the distances indicates that sexual assault is the only type of crime which possesses a buffer zone. The results of statistical analysis show that young people are more mobile than older suspects and that men travel a greater distance than women. Surprisingly, the distance does not differ significantly according to season and time of day. Finally, compared to the other criminal offenders, those who have committed a robbery traveled the greatest distances.

Fundação de Amparo a Pesquisa do Estado de Minas Gerais / The main goal of a images retrieval system is to obtain images from a collection that assist a need of the user. To achieve this objective, in generally, the systems of retrieval of images calculate the similarity between the user's need represented by a query and representations of the images of the collection. Such an objective is dicult of being obtain due to the subjectivity of the similarity concept among images, because a same image can be interpreted in dierent ways by dierent people. In the attempt of solving this problem the content based image retrieval systems explore the characteristics of low level color, forms and texture in the calculation of the similarity among the images. A problem of this approach is that in most of the systems the calculation of the similarity is accomplished being compared the query image with all of the images of the collection, turning the dicult and slow processing. Considering the indexation of characteristics of low level of partitions of digital images mapped to an inverted index, this work looks for improvements in the acting of the processing of querys and improve in the precision considering the group of images retrieval in great bases of data. We used an approach based in inverted index that is here adapted for partitions images. In this approach the concept of term of the retrieval textual, main element of the indexation, it is used in the work as characteristic of partitions of images for the indexation. Experiments show improvement in the quality of the precision using two collections of digital images. / O principal objetivo de um sistema de recuperação de imagens é obter imagens de uma coleção que atendam a uma necessidade do usuário. Para atingir esse objetivo, em geral, os sistemas de recuperação de imagens calculam a similaridade entre a necessidade do usuário, representada por uma consulta, e representações das imagens da coleção. Tal objetivo é difícil de ser alcançado devido à subjetividade do conceito de similaridade entre imagens, visto que uma mesma imagem pode ser interpretada de formas diferentes por pessoas distintas. Na tentativa de resolver este problema os sistemas de recuperação de imagens por conteúdo exploram as características de baixo nível cor, forma e textura no cálculo da similaridade entre as imagens. Um problema desta abordagem é que na maioria dos sistemas o cálculo da similaridade é realizado comparando-se a imagem de consulta com todas as imagens da coleção, tornando o processamento difícil e lento. Considerando a indexação de características de baixo nível de partições de imagens digitais mapeadas para um índice invertido, este trabalho busca melhorias no desempenho do processamento de consultas e ganho na precisão considerando o conjunto de imagens recuperadas em grandes bases de dados. Utilizamos uma abordagem baseada em índice invertido, que é aqui adaptada para imagens particionadas. Nesta abordagem o conceito de termo da recuperação textual, principal elemento da indexação, é utilizado no trabalho como característica de partições de imagens para a indexação. Experimentos mostram ganho na qualidade da precisão usando duas coleções de imagens digitais. / Mestre em Ciência da Computação

Cluster and discriminant analysis belong to basic classification methods. Using cluster analysis can be a disordered group of objects organized into several internally homogeneous classes or clusters. Discriminant analysis creates knowledge based on the jurisdiction of existing classes classification rule, which can be then used for classifying units with an unknown group membership. The aim of this thesis is a comparison of discriminant analysis and different methods of cluster analysis. To reflect the distances between objects within each cluster, squeared Euclidean and Mahalanobis distances are used. In total, there are 28 datasets analyzed in this thesis. In case of leaving correlated variables in the set and applying squared Euclidean distance, Ward´s method classified objects into clusters the most successfully (42,0 %). After changing metrics on the Mahalanobis distance, the most successful method has become the furthest neighbor method (37,5 %). After removing highly correlated variables and applying methods with Euclidean metric, Ward´s method was again the most successful in classification of objects (42,0%). From the result implies that cluster analysis is more precise when excluding correlated variables than when leaving them in a dataset. The average result of discriminant analysis for data with correlated variables and also without correlated variables is 88,7 %.

This master's thesis deals with the problems of anomalies detection in data from clinical trials and medical registries. The purpose of this work is to perform literary research about quality of data in clinical trials and to design a personal algorithm for detection of anomalous records based on machine learning methods in real clinical data from current or completed clinical trials or medical registries. In the practical part is described the implemented algorithm of detection, consists of several parts: import of data from information system, preprocessing and transformation of imported data records with variables of different data types into numerical vectors, using well known statistical methods for detection outliers and evaluation of the quality and accuracy of the algorithm. The result of creating the algorithm is vector of parameters containing anomalies, which has to make the work of data manager easier. This algorithm is designed for extension the palette of information system functions (CLADE-IS) on automatic monitoring the quality of data by detecting anomalous records.