No description available.

There are a number of clinical options available for speech-language pathologists to choose from to analyze a child's phonological system, select treatment targets, and design intervention. Frequently, each of these areas of clinical options is viewed independently of one another or approached within an eclectic framework. In this article, an integrated and systemic approach is presented which assumes that a dynamic interaction exists among assessment, target selection, and intervention. Systemic Phonological Assessment of Child Speech, the distance metric approach to target selection, and the multiple oppositions treatment approach are described, with examples provided for each component. Finally, a case study is presented that examines the systemic approach of multiple oppositions relative to the approach of minimal pairs.

<p>Predmet istraživanja u doktorskoj disertaciji su metode za egzistenciju i konstrukciju nepokretne tačke za jednoznačna i višeznačna preslikavanja kontraktivnog tipa u metričkom i generalizovanim metričkim prostorima (konveksan metrički, fazi metrički i fazi G metrički prostor).</p> / <p>The subject of research in the doctoral dissertation is the methods for the existence and construction of a fixed point for the single and multivalued mappings of a contraction type in metric and in generalized spaces(convex metric spaces, fuzzy metric spaces and fuzzy G-metric spaces).</p>

Cette thèse se focalise sur l'apprentissage de distance pour la comparaison d'images ou de pages Web. Les distances (ou métriques) sont exploitées dans divers contextes de l'apprentissage automatique et de la vision artificielle tels que la recherche des k plus proches voisins, le partitionnement, les machines à vecteurs de support, la recherche d'information/images, la visualisation etc. Nous nous intéressons dans cette thèse à l'apprentissage de fonction de distance paramétrée par une matrice symétrique semi-définie positive. Ce modèle, appelé (par abus) apprentissage de distance de Mahalanobis, consiste à apprendre une transformation linéaire des données telle que la distance euclidienne dans l'espace projeté appris satisfasse les contraintes d'apprentissage.Premièrement, nous proposons une méthode basée sur la comparaison de distances relatives qui prend en compte des relations riches entre les données, et exploite des similarités entre quadruplets d'exemples. Nous appliquons cette méthode aux attributs relatifs et à la classification hiérarchique d'images.Deuxièmement, nous proposons une nouvelle méthode de régularisation qui permet de contrôler le rang de la matrice apprise, limitant ainsi le nombre de paramètres indépendants appris et le sur-apprentissage. Nous montrons l'intérêt de notre méthode sur des bases synthétiques et réelles d'identification de visage.Enfin, nous proposons une nouvelle méthode de détection automatique de changement dans les pages Web, dans un contexte d'archivage. Pour cela, nous utilisons les relations de distance temporelle entre différentes versions d'une même page Web. La métrique apprise de façon entièrement non supervisée détecte les régions d'intérêt de la page et ignore le contenu non informatif tel que les menus et publicités. Nous montrons l'intérêt de la méthode sur différents sites Web. / This thesis focuses on distance metric learning for image and webpage comparison. Distance metrics are used in many machine learning and computer vision contexts such as k-nearest neighbors classification, clustering, support vector machine, information/image retrieval, visualization etc. In this thesis, we focus on Mahalanobis-like distance metric learning where the learned model is parametered by a symmetric positive semidefinite matrix. It learns a linear tranformation such that the Euclidean distance in the induced projected space satisfies learning constraints.First, we propose a method based on comparison between relative distances that takes rich relations between data into account, and exploits similarities between quadruplets of examples. We apply this method on relative attributes and hierarchical image classification. Second, we propose a new regularization method that controls the rank of the learned matrix, limiting the number of independent parameters and overfitting. We show the interest of our method on synthetic and real-world recognition datasets. Eventually, we propose a novel Webpage change detection framework in a context of archiving. For this purpose, we use temporal distance relations between different versions of a same Webpage. The metric learned in a totally unsupervised way detects important regions and ignores unimportant content such as menus and advertisements. We show the interest of our method on different Websites.

No description available.

Kerr metric is one of the most well-known and useful exact solutions of Einstein equations. We study various geometric properties of the Kerr spacetime in order to gain intuition for its spatial shape. In the review part we summarize basic features of the Kerr geometry, we write down Carter equations for geodesic motion in the Kerr spacetime, and we introduce kinematic characteristics of time-like and light-like congruences, such as expansion, shear and twist. In the second part of the thesis we calculate scalars for acceleration, expansion, shear and twist - and plot the corresponding "equipotential" surfaces - for several privi- leged congruences, namely the Carter observers, the static observers, the zero-angular- momentum observers, the principal null congruence and the recently found non-twisting null congruence(s). We also draw surfaces radially equidistant from the horizon and sur- faces spatially orthogonal to the PNC and to the twist-free congruences, as well as the surfaces of constant energy and redshift for the important time-like congruences. 1

This thesis contains a theoretical basis for MANET networks. The main focus of the thesis is principles of these networks, their routing protocols and especially on Ad hoc On-Demand Distance Vector (AODV), implementation of this protocol and implementation of new mechanis for peer selection. Thesis contains ETX metric basic and implementation of this metric to AODV protocol. There is a demonstration of simulation of AODV protocol and simulation of AODV-ETX protocol. Simulations are run in Network Simulator 3. AODV and AODV-ETX comparasion are included in thesis.

This work is focused on the design of an algorithm for run-time verification over requirements given as formulas in metric temporal logic (MTL). Tree structure is used for verification of these requirements, which is similar to run of alternating timed automata from which the final algorithm is derivated. Designed algorithm is able to verify given MTL formulas over the runs of a program without a need to remember the whole program's trace. This allows to monitor a given program on potentially infinite runs.

京都大学 / 0048 / 新制・課程博士 / 博士(情報学) / 甲第18482号 / 情博第533号 / 新制||情||94(附属図書館) / 31360 / 京都大学大学院情報学研究科知能情報学専攻 / (主査)教授 美濃 導彦, 教授 河原 達也, 教授 中村 裕一 / 学位規則第4条第1項該当 / Doctor of Informatics / Kyoto University / DFAM

京都大学 / 0048 / 新制・課程博士 / 博士(情報学) / 甲第19417号 / 情博第596号 / 新制||情||104(附属図書館) / 32442 / 京都大学大学院情報学研究科知能情報学専攻 / (主査)教授 山本 章博, 教授 黒橋 禎夫, 教授 鹿島 久嗣, 准教授 Cuturi Marco / 学位規則第4条第1項該当 / Doctor of Informatics / Kyoto University / DFAM