L'imagerie cérébrale connaît un intérêt grandissant, en tant que phénotype intermédiaire, dans la compréhension du chemin complexe qui relie les gènes à un phénotype comportemental ou clinique. Dans ce contexte, un premier objectif est de proposer des méthodes capables d'identifier la part de variabilité génétique qui explique une certaine part de la variabilité observée en neuroimagerie. Les approches univariées classiques ignorent les effets conjoints qui peuvent exister entre plusieurs gènes ou les covariations potentielles entre régions cérébrales.Notre première contribution a été de chercher à améliorer la sensibilité de l'approche univariée en tirant avantage de la nature multivariée des données génétiques, au niveau local. En effet, nous adaptons l'inférence au niveau du cluster en neuroimagerie à des données de polymorphismes d'un seul nucléotide (SNP), en cherchant des clusters 1D de SNPs adjacents associés à un même phénotype d'imagerie. Ensuite, nous prolongeons cette idée et combinons les clusters de voxels avec les clusters de SNPs, en utilisant un test simple au niveau du "cluster 4D", qui détecte conjointement des régions cérébrale et génomique fortement associées. Nous obtenons des résultats préliminaires prometteurs, tant sur données simulées que sur données réelles.Notre deuxième contribution a été d'utiliser des méthodes multivariées exploratoires pour améliorer la puissance de détection des études d'imagerie génétique, en modélisant la nature multivariée potentielle des associations, à plus longue échelle, tant du point de vue de l'imagerie que de la génétique. La régression Partial Least Squares et l'analyse canonique ont été récemment proposées pour l'analyse de données génétiques et transcriptomiques. Nous proposons ici de transposer cette idée à l'analyse de données de génétique et d'imagerie. De plus, nous étudions différentes stratégies de régularisation et de réduction de dimension, combinées avec la PLS ou l'analyse canonique, afin de faire face au phénomène de sur-apprentissage dû aux très grandes dimensions des données. Nous proposons une étude comparative de ces différentes stratégies, sur des données simulées et des données réelles d'IRM fonctionnelle et de SNPs. Le filtrage univarié semble nécessaire. Cependant, c'est la combinaison du filtrage univarié et de la PLS régularisée L1 qui permet de détecter une association généralisable et significative sur les données réelles, ce qui suggère que la découverte d'associations en imagerie génétique nécessite une approche multivariée. / Brain imaging is increasingly recognised as an interesting intermediate phenotype to understand the complex path between genetics and behavioural or clinical phenotypes. In this context, a first goal is to propose methods to identify the part of genetic variability that explains some neuroimaging variability. Classical univariate approaches often ignore the potential joint effects that may exist between genes or the potential covariations between brain regions. Our first contribution is to improve the sensitivity of the univariate approach by taking advantage of the multivariate nature of the genetic data in a local way. Indeed, we adapt cluster-inference techniques from neuroimaging to Single Nucleotide Polymorphism (SNP) data, by looking for 1D clusters of adjacent SNPs associated with the same imaging phenotype. Then, we push further the concept of clusters and we combined voxel clusters and SNP clusters, by using a simple 4D cluster test that detects conjointly brain and genome regions with high associations. We obtain promising preliminary results on both simulated and real datasets .Our second contribution is to investigate exploratory multivariate methods to increase the detection power of imaging genetics studies, by accounting for the potential multivariate nature of the associations, at a longer range, on both the imaging and the genetics sides. Recently, Partial Least Squares (PLS) regression or Canonical Correlation Analysis (CCA) have been proposed to analyse genetic and transcriptomic data. Here, we propose to transpose this idea to the genetics vs. imaging context. Moreover, we investigate the use of different strategies of regularisation and dimension reduction techniques combined with PLS or CCA, to face the overfitting issues due to the very high dimensionality of the data. We propose a comparison study of the different strategies on both a simulated dataset and a real fMRI and SNP dataset. Univariate selection appears to be necessary to reduce the dimensionality. However, the generalisable and significant association uncovered on the real dataset by the two-step approach combining univariate filtering and L1-regularised PLS suggests that discovering meaningful imaging genetics associations calls for a multivariate approach.

Submitted by Valquíria Barbieri (kikibarbi@hotmail.com) on 2018-05-11T20:59:15Z No. of bitstreams: 1 DISS_2015_Karen Janones da Rocha.pdf: 4327569 bytes, checksum: 1207959001ffdfc221d56edf601d488a (MD5) / Approved for entry into archive by Jordan (jordanbiblio@gmail.com) on 2018-05-24T14:50:15Z (GMT) No. of bitstreams: 1 DISS_2015_Karen Janones da Rocha.pdf: 4327569 bytes, checksum: 1207959001ffdfc221d56edf601d488a (MD5) / Made available in DSpace on 2018-05-24T14:50:15Z (GMT). No. of bitstreams: 1 DISS_2015_Karen Janones da Rocha.pdf: 4327569 bytes, checksum: 1207959001ffdfc221d56edf601d488a (MD5) Previous issue date: 2015-02-06 / CAPES / O objetivo geral do presente estudo foi caracterizar um fragmento secundário de Floresta Estacional Semidecidual localizado em Tapurah-MT, quanto a sua estrutura e composição florestal, verificar a formação de grupos florísticos e, ainda, explorar possíveis relações com o ambiente. Aplicou-se o método de área fixa com conglomerados retangulares de dimensões de 10 x 250 m, foram alocados e medidos cinco conglomerados com cinco subunidades cada de 10 X 50 m. Em cada subunidade amostral foi considerada todas as espécies arbóreas e arbustivas com diâmetro à altura do peito (DAP) superior ou igual a 10 cm. A composição florística foi analisada quanto ao número de famílias, gêneros e espécies botânicas encontradas no levantamento do componente arbóreo e a suficiência amostral do levantamento florístico foi verificada pelo procedimento Bootstrap. A similaridade florística entre as subunidades amostrais foi obtida através do Índice de Jaccard e a diversidade de espécies nas subunidades amostrais foi medida pelo Índice de Shannon (H’) e pelo Índice de Equabilidade de Pielou (J’). A caracterização da estrutura horizontal da vegetação foi feita a partir dos parâmetros fitossociológicos e a estrutura diamétrica pelo procedimento de Spiegel. A presença de grupos florísticos foi verificada pelo método de associação das espécies e o número de grupos foi estabelecido pelo coeficiente de concordância de Kendall, onde para cada grupo florístico foi analisada a estrutura horizontal, o padrão de distribuição espacial das espécies pelo índice de Payandeh e a estrutura diamétrica dos indivíduos pelo procedimento de Spiegel. A construção da matriz das variáveis edáficas foi realizada através de uma análise preliminar para identificar variáveis semelhantes entre as subunidades amostrais, as quais não apresentaram influência foram retiradas. A correlação entre os dados de vegetação e dados ambientais foi realizada por meio da Análise de Correlação Canônica, que permitiu confirmar se os nutrientes do solo influenciam na presença das espécies e pela Análise de Redundância Canônica para avaliar quais as variáveis ambientais apresentaram maior influência sobre os indivíduos. No fragmento foi verificada uma alta variabilidade florística e estrutural, que pode ser explicada pelos históricos de perturbação local a que este fragmento foi submetido no passado. De uma forma geral, a vegetação corresponde a de florestas secundárias jovens e apresenta uma comunidade estável e autorregenerativa, além de preservar características da estrutura original. Através da análise de agrupamento foi verificado que as características autoecológicas das espécies assim como os DAP’s médios de cada espécie foram os principais responsáveis pela associação e similaridade entre os grupos. Também foi verificada que apesar das perturbações no ambiente que salientam a saturação do sítio florestal, o fragmento está se recuperando. A heterogeneidade das variáveis edáficas relacionadas influencia no comportamento florístico-estrutural do fragmento secundário de Floresta Estacional Semidecidual. Sendo, as espécies das famílias Fabaceae, Lauraceae, Moraceae e Vochysiaceae as mais influentes para o presente estudo. Destacando a Qualea paraensis Ducke quanto à importância ecológica e a sua adaptabilidade ao ambiente. / The general objective of this study was to characterize a secondary fragment of semideciduous forest located in Tapurah-MT, as its structure and forest composition, verify the formation of floristic groups and also explore possible relationships with the environment. Was applied the fixed area method with five rectangular clusters of 10 x 250 m, they were measured and allocated to five subunits of 10 x 50 m each. In each sample subunit was considered all tree and shrub species with diameter at breast height (DBH) greater than or equal to 10 cm. The floristic composition was analyzed for the number of families, genera and plant species found in the survey of the tree component and sampling sufficiency of floristic survey was tested by bootstrap procedure. The floristic similarity between plots was obtained through the Jaccard index and the diversity of species in the sample subunits was measured by the Shannon Index (H') and equability index of Pielou (J'). The characterization of the horizontal structure of vegetation was made from the phytosociological parameters and the structure diameter by Spiegel procedure. The presence of floristic groups was verified by the association method of species and the number of groups was established by Kendall concordance coefficient, where for each floristic group was analyzed horizontal structure, the pattern of spatial distribution of species by Payandeh index and the diameter distribution of individuals by Spiegel procedure. The construction of the matrix of the soil variables was performed in a preliminary analysis to identify variables similar to the sample subunits, which showed no influence were dropped. The correlation between the data of vegetation and environmental data was performed by Canonical Correlation Analysis, which allowed confirm that soil nutrients influence the presence of the species and the Canonical Redundancy Analysis to evaluate which environmental variables had the greatest influence on the individuals. In the studied fragment was observed high variability floristic and structural, which can be explained by historical local disturbance that this fragment was in the past. In general, the vegetation corresponds to young secondary forests and presents a stable and self-regenerative community, besides preserving the original structure characteristics. Through cluster analysis it was found that the ecological self characteristics of the species as well as the average DBH of each species were mainly responsible for the association and similarity between the groups. We also observed that despite the disturbances in the environment that emphasize the saturation of forest site, the fragment is recovering. The soil variables heterogeneity related influence the floristic-structural behavior of the secondary fragment of semideciduous forest. Being, the species of the families: Fabaceae, Lauraceae, Moraceae and Vochysiaceae the most influential for the present study. Highlighting the Qualea paraensis Ducke about its ecological significance and adaptability to the environment.

The goal of the work is to provide monetary valuation of changes in visual aspects of the landscape as a result of construction of an additional wind turbine in the village Maletín. For a suitable method for achieving the goal is being selected the contingent valuation method. A key element of this method is being considered the carefully compiled questionnaire, on which basis is made the quantification and evaluation of collected data. The representative sample consists of 112 households and the selected payment method is the increase of the monthly bill for electricity. The questionnaire reports that 54.3% of households consider the impact of wind turbines on the landscape Maletín to be positive. With the construction of additional wind turbine agree less than 74.3% of households and the most common reason is to obtain grants for the village and to produce cleaner energy from wind turbines. With the construction of new wind turbine while increasing monthly bill agrees 28.6% of all households living in the village Maletín. Estimation of changes in a welfare, thus improving the quality of the environment, is based on estimated central values, that has been calculated from selected characteristics and nonparametric estimation. The average household's willingness to pay for construction of wind turbine is estimated to be between 77 CZK - 200 CZK per month.

<p>A Real-Time Brain-Computer Interface is a technical system classifying increased or decreased brain activity in Real-Time between different body movements, actions performed by a person. Focus in this thesis will be on testing algorithms and settings, finding the initial time interval and how increased activity in the brain can be distinguished and satisfyingly classified. The objective is letting the system give an output somewhere within 250ms of a thought of an action, which will be faster than a persons reaction time. </p><p>Algorithms in the preprocessing were Blind Signal Separation and the Fast Fourier Transform. With different frequency and time interval settings the algorithms were tested on an offline Electroencephalographic data file based on the "Ten Twenty" Electrode Application System, classified using an Artificial Neural Network. </p><p>A satisfying time interval could be found between 125-250ms, but more research is needed to investigate that specific interval. A reduction in frequency resulted in a lack of samples in the sample window preventing the algorithms from working properly. A high frequency is therefore proposed to help keeping the sample window small in the time domain. Blind Signal Separation together with the Fast Fourier Transform had problems finding appropriate correlation using the Ten-Twenty Electrode Application System. Electrodes should be placed more selectively at the parietal lobe, in case of requiring motor responses.</p>

A Real-Time Brain-Computer Interface is a technical system classifying increased or decreased brain activity in Real-Time between different body movements, actions performed by a person. Focus in this thesis will be on testing algorithms and settings, finding the initial time interval and how increased activity in the brain can be distinguished and satisfyingly classified. The objective is letting the system give an output somewhere within 250ms of a thought of an action, which will be faster than a persons reaction time. Algorithms in the preprocessing were Blind Signal Separation and the Fast Fourier Transform. With different frequency and time interval settings the algorithms were tested on an offline Electroencephalographic data file based on the "Ten Twenty" Electrode Application System, classified using an Artificial Neural Network. A satisfying time interval could be found between 125-250ms, but more research is needed to investigate that specific interval. A reduction in frequency resulted in a lack of samples in the sample window preventing the algorithms from working properly. A high frequency is therefore proposed to help keeping the sample window small in the time domain. Blind Signal Separation together with the Fast Fourier Transform had problems finding appropriate correlation using the Ten-Twenty Electrode Application System. Electrodes should be placed more selectively at the parietal lobe, in case of requiring motor responses.

Studentų pažangą geriausiai nusako jų studijų dalykų bei bakalauro darbo vertinimai. Šiaulių universitete Matematikos ir informatikos fakultete Matematikos bei Matematikos ir informatikos bakalauro studijų programose pagrindiniai studijų dalykai yra: Matematinė analizė, Algebra, Fizika, Geometrija, Kompiuterinės matematikos sistemos ir Programavimo pagrindai. Bakalauro darbe analizuojame Šiaulių universiteto Matematikos ir informatikos fakulteto Matematikos bei Matematikos ir informatikos bakalauro studijų programų studentų įstojusių 2004–2008 pasiekimus. Šio darbo tikslas yra nustatyti, kuris iš pagrindinių studijų dalykų vertinimų labiausiai susijęs su baigiamojo bakalauro darbo vertinimu. Šiam ryšiui nustatyti naudojame koreliacinę analizę bei tiesinę regresiją. / Students’ advancement is described by their evaluation of study subjects and Bachelor's work. Basic subjects in Bachelor's degree program at Siauliai University, Faculty of Mathematics and Informatics are: Mathematical analysis, Algebra, Geometry, Physics, Computer mathematics system and Programming fundamentals. In Bachelor's work, we investigate a relation between 6 study subjects and Bachelor's work evaluations of students who entranced in 2004–2008. To describe this relation we use correlation analysis and linear regression.

The development of modern information technology has enabled collecting data of unprecedented size and complexity. Examples include web text data, microarray & proteomics, and data from scientific domains (e.g., meteorology). To learn from these high dimensional and complex data, traditional machine learning techniques often suffer from the curse of dimensionality and unaffordable computational cost. However, learning from large-scale high-dimensional data promises big payoffs in text mining, gene analysis, and numerous other consequential tasks. Recently developed sparse learning techniques provide us a suite of tools for understanding and exploring high dimensional data from many areas in science and engineering. By exploring sparsity, we can always learn a parsimonious and compact model which is more interpretable and computationally tractable at application time. When it is known that the underlying model is indeed sparse, sparse learning methods can provide us a more consistent model and much improved prediction performance. However, the existing methods are still insufficient for modeling complex or dynamic structures of the data, such as those evidenced in pathways of genomic data, gene regulatory network, and synonyms in text data. This thesis develops structured sparse learning methods along with scalable optimization algorithms to explore and predict high dimensional data with complex structures. In particular, we address three aspects of structured sparse learning: 1. Efficient and scalable optimization methods with fast convergence guarantees for a wide spectrum of high-dimensional learning tasks, including single or multi-task structured regression, canonical correlation analysis as well as online sparse learning. 2. Learning dynamic structures of different types of undirected graphical models, e.g., conditional Gaussian or conditional forest graphical models. 3. Demonstrating the usefulness of the proposed methods in various applications, e.g., computational genomics and spatial-temporal climatological data. In addition, we also design specialized sparse learning methods for text mining applications, including ranking and latent semantic analysis. In the last part of the thesis, we also present the future direction of the high-dimensional structured sparse learning from both computational and statistical aspects.

Ce mémoire traite de l'acoustique de la clarinette et du rôle de l'anche, résumant des travaux menés entre 2001 et 2018 sur divers sujets :I) Étude de modèles analytiques élémentaire focalisée sur : 1) le rôle des pertes. 2) les cartes itérées, mettant en évidence divers régimes de fonctionnement, utiles aussi pour la pédagogie instrumentale. II) Étude de caractérisation des anches : 1) Étude dynamique des résonances de l'anche réalisée par holographie. Elle conduit à un modèle de matériau viscoélastique expliquant certaines différences observées dans les fréquences des 15 premiers modes de l'anche. 2) Étude statique des caractéristiques mécaniques et aérauliques de l'excitateur (anche+bec+lèvre). La méthode mesure précisément la quantité d'air entrant dans l'instrument en fonction de la pression de lèvre et d'air. III) Synthèse sonore par modèle physique en temps réel : 1) Modélisation mécanique et aéraulique de l'anche, d'après mesure. Le modèle de ressort raidissant non linéaire proposé autorise une simulation dynamique efficace. 2) Estimation modale de l'impédance d'entrée (mesurée) des instruments à vent. On montre les techniques de conception de filtres numériques précis et passifs à toute fréquence. 3) Modélisation et simulation instruments à vent au moyen de guide-ondes, par estimation modale, implémentée dans un logiciel en C++. IV) Une étude de jouabilité d'un panel de 40 anches par analyse canonique des corrélations révèle des liens statistiquement solides entre mesures physiques, évaluations subjectives et synthèse sonore. Elle autorise une caractérisation des anches pouvant être réalisé par le fabricant, selon au moins 4 facteurs indépendants. / This thesis deals with the acoustics of the clarinet and the role of the reed, summarizing studies carried out between 2001 and 2018 on various topics : I) Study of elementary analytical models, focused on 1) role of losses. 2) iterated maps, highlighting various operating regimes, which are also useful for the instrumental pedagogy. II) Reed characterization study : 1) Dynamic study of the reed resonances, by holography. It leads to a model of viscoelastic material explaining some differences observed in the frequencies of the first 15 modes of the reed. 2) Static study of the mechanical and aeraulic characteristics of the exciter (reed + mouthpiece + lip). The method accurately measures the airflow entering the instrument as a function of lip and air pressure. III) Sound synthesis by physical model in real time : 1) Mechanical and aeraulic modeling of the reed, according to measurements. The proposed nonlinear stiffening spring model allows for an efficient dynamic simulation. 2) Modal estimation of the (measured) input impedance of wind instruments. Design techniques for accurate digital filters, passive at any frequency, are described. 3) Modal estimation and simulation of wind instruments by waveguides, implemented in C ++ software. IV) A playability study of a panel of 40 reeds by canonical correlation analysis reveals statistically strong links between physical measurements, subjective evaluations and sound synthesis. It allows a characterization of the reeds that can be made by the manufacturer, according to at least 4 independent factors.

The dissertation thesis focuses on the topic of construction of new questionnaire, which is developed from four already existing questionnaires of activities of daily living. This new questionnaire summarizes strengths of those four and submits only those activities, which are affected at the early stage of Alzheimer's dementia. The topic is introduced in the broad context of social sciences, medical science and also submits the practical issues, considering effects of Alzheimer's disease to life of patient and his closest ones. New questionnaire, which is the result of empirical research, is based on correlation analysis of three commonly used screening cognitive tests and four questionnaires which evaluate activities of daily life, which are, used as best practice in the Counseling Center for Memory Disorders Clinic of Neurology of Faculty Hospital Kralovske Vinohrady in Prague. The research sample consists of patiens, who are affected with Alzheimer's disease already. That means, that the new questionnaire can be used as a tool for those, who are the patient's closest ones for purpose of screening and reviewing abilities of daily living over time. The questionnaire also presents comprehensively compiled a list of activities of daily living which Alzheimer's disease affects in early stage and this list...

The study was aimed at exploring the relationship between poverty and aggravated robbery in Limpopo Province. Sampled secondary data of aggravated robbery of- fenders, obtained from the South African Police (SAPS), Polokwane, was used in the analysis. From empirical researches on poverty and crime, there are some deductions that vulnerability to crime is increased by poverty. Poverty set was categorised by gender, employment status, marital status, race, age and educational attainment. Variables for aggravated robbery were house robbery, bank robbery, street/common robbery, carjacking, truck hijacking, cash-in-transit and business robbery. Canonical correlation analysis was used to make some inferences about the relationship of these two sets. The results revealed a signi cant positive correlation of 0.219(p-value = 0.025) between poverty and aggravated robbery at ve per cent signi cance level. Of the thirteen variables entered into the poverty-aggravated model, ve emerged as sta- tistically signi cant. These were gender, marital status, employment status, common robbery and business robbery. / Mathematical Sciences / M. Sc. (Statistics)