Nomenclatura na língua portuguesa em cromatografia multidimensional abrangente

Comprehensive Multidimensional Chromatography is a relatively new analytic technique, which is receiving growing attention in many parts of the world, including recently in Brazil. This work presents terms in Portuguese which are commonly used in Comprehensive Multidimensional Chromatography in order to help standardize the vocabulary employed in this area in the scientific literature. It also includes some symbols, their nominations, and explanation of some terms, whenever necessary. This proposal does not intend to be comprehensive or definitive; on the contrary, it intends to be a first step in the process of establishing a standardized nomenclature, serving as a base for a further sound discussion in the scientific community realm.

Análisis psicométrico de la escala multidimensional de autoconcepto AF5 en una muestra de adolescentes y adultos de Cataluña

Psychometric analysis of the AF5 multidimensional scale of self-concept in a sample of adolescents and adults in Catalonia. The aim of this study is to carry out a psychometric study of the AF5 scale in a sample of 4.825 Catalan subjects from 11 to 63 years-old. They are students from secondary compulsory education (ESO), from high school, middle-level vocational training (CFGM) and from the university. Using a principal component analysis (PCA) the theoretical validity of the components is established and the reliability of the instrument is also analyzed. Differential analyses are performed by gender and normative group using a 2 6 factorial design. The normative group variable includes the different levels classifi ed into 6 sub-groups: university, post-compulsory secondary education (high school and CFGM), 4th of ESO, 3rd of ESO, 2nd of ESO and 1st of ESO. The results indicate that the reliability of the Catalan version of the scale is similar to the original scale. The factorial structure also fi ts with the original model established beforehand. Signifi cant differences by normative group in the four components of self-concept explored (social, family, academic/occupational and physical) are observed. By gender, signifi cant differences appear in the component of physical self-concept, academic and social but not in the family component

Lenguaje y Teoría de la mente: una aproximación multidimensional

El propósito de este trabajo es realizar una puesta al día sobre las relaciones entre el desarrollo del lenguaje y el desarrollo de la Teoría de la Mente. Entre las hipótesis propuestas para conceptualizar dichas relaciones, realizamos un examen más exhaustivo de aquellos modelos que apoyan una implicación directa entre lenguaje y Teoría de la Mente. En este contexto, en primer lugar subrayamos la necesidad de ampliar dicha noción para incluir habilidades anteriores y posteriores a la comprensión de la falsa creencia. En segundo lugar, examinamos las diferentes hipótesis acerca de los aspectos del lenguaje más vinculados al desarrollo sociocognitivo, y las principales evidencias empíricas que las sustentan. Finalmente, discutimos un modelo de causalidad recíproca donde los vínculos entre lenguaje y Teoría de la Mente variarán según el momento del desarrollo considerado

On convergence of transforms based on parabolic scaling

This thesis studies properties of transforms based on parabolic scaling, like Curvelet-, Contourlet-, Shearlet- and Hart-Smith-transform. Essentially, two di erent questions are considered: How these transforms can characterize H older regularity and how non-linear approximation of a piecewise smooth function converges. In study of Hölder regularities, several theorems that relate regularity of a function f : R2 → R to decay properties of its transform are presented. Of particular interest is the case where a function has lower regularity along some line segment than elsewhere. Theorems that give estimates for direction and location of this line, and regularity of the function are presented. Numerical demonstrations suggest also that similar theorems would hold for more general shape of segment of low regularity. Theorems related to uniform and pointwise Hölder regularity are presented as well. Although none of the theorems presented give full characterization of regularity, the su cient and necessary conditions are very similar. Another theme of the thesis is the study of convergence of non-linear M ─term approximation of functions that have discontinuous on some curves and otherwise are smooth. With particular smoothness assumptions, it is well known that squared L2 approximation error is O(M-2(logM)3) for curvelet, shearlet or contourlet bases. Here it is shown that assuming higher smoothness properties, the log-factor can be removed, even if the function still is discontinuous.

Evaluating multidimensional visualization techniques in data mining tasks

Visual data mining (VDM) tools employ information visualization techniques in order to represent large amounts of high-dimensional data graphically and to involve the user in exploring data at different levels of detail. The users are looking for outliers, patterns and models – in the form of clusters, classes, trends, and relationships – in different categories of data, i.e., financial, business information, etc. The focus of this thesis is the evaluation of multidimensional visualization techniques, especially from the business user’s perspective. We address three research problems. The first problem is the evaluation of projection-based visualizations with respect to their effectiveness in preserving the original distances between data points and the clustering structure of the data. In this respect, we propose the use of existing clustering validity measures. We illustrate their usefulness in evaluating five visualization techniques: Principal Components Analysis (PCA), Sammon’s Mapping, Self-Organizing Map (SOM), Radial Coordinate Visualization and Star Coordinates. The second problem is concerned with evaluating different visualization techniques as to their effectiveness in visual data mining of business data. For this purpose, we propose an inquiry evaluation technique and conduct the evaluation of nine visualization techniques. The visualizations under evaluation are Multiple Line Graphs, Permutation Matrix, Survey Plot, Scatter Plot Matrix, Parallel Coordinates, Treemap, PCA, Sammon’s Mapping and the SOM. The third problem is the evaluation of quality of use of VDM tools. We provide a conceptual framework for evaluating the quality of use of VDM tools and apply it to the evaluation of the SOM. In the evaluation, we use an inquiry technique for which we developed a questionnaire based on the proposed framework. The contributions of the thesis consist of three new evaluation techniques and the results obtained by applying these evaluation techniques. The thesis provides a systematic approach to evaluation of various visualization techniques. In this respect, first, we performed and described the evaluations in a systematic way, highlighting the evaluation activities, and their inputs and outputs. Secondly, we integrated the evaluation studies in the broad framework of usability evaluation. The results of the evaluations are intended to help developers and researchers of visualization systems to select appropriate visualization techniques in specific situations. The results of the evaluations also contribute to the understanding of the strengths and limitations of the visualization techniques evaluated and further to the improvement of these techniques.

Hipsometric relationship modeling using data sampled in tree scaling and inventory plots

This work evaluated eight hypsometric models to represent tree height-diameter relationship, using data obtained from the scaling of 118 trees and 25 inventory plots. Residue graphic analysis and percent deviation mean criteria, qui-square test precision, residual standard error between real and estimated heights and the graybill f test were adopted. The identity of the hypsometric models was also verified by applying the F(Ho) test on the plot data grouped to the scaling data. It was concluded that better accuracy can be obtained by using the model prodan, with h and d1,3 data measured in 10 trees by plots grouped into these scaling data measurements of even-aged forest stands.

Challenges in scaling agile software development in offshoring environment

Corporate decision to scale Agile Software development methodologies in offshoring environment has been obstructed due to possible challenges in scaling agile as agile methodologies are regarded to be suitable for small project and co-located team only. Although model such as Agile Scaling Model (ASM) has been developed for scaling Agile with different factors, inabilities of companies to figure out challenges and addressing them lead to failure of project rather than gaining the benefits of using agile methodologies. This failure can be avoided, when scaling agile in IT offshoring environment, by determining key challenges associated in scaling agile in IT offshoring environment and then preparing strategies for addressing those key challenges. These key challenges in scaling agile with IT offshoring environment can be determined by studying issues related with Offshoring and Agile individually and also considering the positive impact of agile methodology in offshoring environment. Then, possible strategies to tackle these key challenges are developed according to the nature of individual challenges and utilizing the benefits of different agile methodologies to address individual situation. Thus, in this thesis, we proposed strategy of using hybrid agile method, which is increasing trend due to adaptive nature of Agile. Determination of the key challenges and possible strategies for tackling those challenges are supported with the survey conducted in the researched organization.

Scaling up stepwise feature introduction to construction of large software systems

Developing software is a difficult and error-prone activity. Furthermore, the complexity of modern computer applications is significant. Hence,an organised approach to software construction is crucial. Stepwise Feature Introduction – created by R.-J. Back – is a development paradigm, in which software is constructed by adding functionality in small increments. The resulting code has an organised, layered structure and can be easily reused. Moreover, the interaction with the users of the software and the correctness concerns are essential elements of the development process, contributing to high quality and functionality of the final product. The paradigm of Stepwise Feature Introduction has been successfully applied in an academic environment, to a number of small-scale developments. The thesis examines the paradigm and its suitability to construction of large and complex software systems by focusing on the development of two software systems of significant complexity. Throughout the thesis we propose a number of improvements and modifications that should be applied to the paradigm when developing or reengineering large and complex software systems. The discussion in the thesis covers various aspects of software development that relate to Stepwise Feature Introduction. More specifically, we evaluate the paradigm based on the common practices of object-oriented programming and design and agile development methodologies. We also outline the strategy to testing systems built with the paradigm of Stepwise Feature Introduction.

Matrix Mind : on managerial reframing in multidimensional problem solving

Det är inte ovanligt att man i organisationer ställs inför problem som inte kan hanteras inom befintlig organisationsstruktur. Skälen kan vara att frågorna har många – ibland konflikterande – dimensioner och perspektiv som samtidigt måste beaktas. I den här avhandlingen studeras vilka tankemönster och föreställningar som fanns när grupper av chefer försökte lösa komplexa problem, som inte hade en naturlig organisatorisk hemvist och hur de omsatte dessa tankemönster i handling. Vad kännetecknade det ledarskap som utövades under problemlösningsprocessen? Avhandlingens empiri hämtas från ledarutvecklingsprogram i två internationellt verksamma företag i Sverige, och omfattar 14 verkliga affärsproblem i dessa företag och den process varigenom de löstes. De 14 seminarierna utgör exempel på hur mångdimensionella frågeställningar framgångsrikt hanteras utanför den befintliga organisationsstrukturen. Studien ger, genom att adressera frågor kring tankesätt och ledningsprocesser, en djupare förståelse för förutsättningarna för detta, och lyfter särskilt fram betydelsen av ett ledarskap som inbegriper begreppen intervention, förmåga och omtolkning. Som ett samlat begrepp introduceras bilden att utöva ledarskapet utifrån ett matrix mind. Att påverka strukturer (i vid mening) och därigenom de förmågor som utvecklas, är del i detta ledarskap. Det sker genom interventioner (ingrepp som påverkar relationer i t ex en grupp) och baserades i den aktuella empirin på uppfattningar om värdet av problematisering, erfarenhetsutbyte och av ett språk, som både beskriver och anger inriktning för aktiviteter. Interventioner i strukturer (och till dem knutna processer) beskriver dock bara delvis detta ledarskap. Att leda med ett matrix mind innefattar också ett nyfiket och kreativt förhållningssätt, och att utifrån detta leda omtolkning av problem. I empirin finns flera exempel på detta. Avhandlingen avser att ge ett bidrag inom såväl organisations- som ledarskapsteori.

Structural and Computational Existence Results for Multidimensional Subshifts

Symbolic dynamics is a branch of mathematics that studies the structure of infinite sequences of symbols, or in the multidimensional case, infinite grids of symbols. Classes of such sequences and grids defined by collections of forbidden patterns are called subshifts, and subshifts of finite type are defined by finitely many forbidden patterns. The simplest examples of multidimensional subshifts are sets of Wang tilings, infinite arrangements of square tiles with colored edges, where adjacent edges must have the same color. Multidimensional symbolic dynamics has strong connections to computability theory, since most of the basic properties of subshifts cannot be recognized by computer programs, but are instead characterized by some higher-level notion of computability. This dissertation focuses on the structure of multidimensional subshifts, and the ways in which it relates to their computational properties. In the first part, we study the subpattern posets and Cantor-Bendixson ranks of countable subshifts of finite type, which can be seen as measures of their structural complexity. We show, by explicitly constructing subshifts with the desired properties, that both notions are essentially restricted only by computability conditions. In the second part of the dissertation, we study different methods of defining (classes of ) multidimensional subshifts, and how they relate to each other and existing methods. We present definitions that use monadic second-order logic, a more restricted kind of logical quantification called quantifier extension, and multi-headed finite state machines. Two of the definitions give rise to hierarchies of subshift classes, which are a priori infinite, but which we show to collapse into finitely many levels. The quantifier extension provides insight to the somewhat mysterious class of multidimensional sofic subshifts, since we prove a characterization for the class of subshifts that can extend a sofic subshift into a nonsofic one.

Scaling analysis of small break experiments in PACTEL

The purpose of this thesis is to study the scalability of small break LOCA experiments. The study is performed on the experimental data, as well as on the results of thermal hydraulic computation performed on TRACE code. The SBLOCA experiments were performed on PACTEL facility situated at LUT. The temporal scaling of the results was done by relating the total coolant mass in the system with the initial break mass flow and using the quotient to scale the experiment time. The results showed many similarities in the behaviour of pressure and break mass flow between the experiments.

A multidimensional measurement approach and analysis of children's motivation for reading, attributional style, and reading achievement

The present study investigates the usefulness of a multi-method approach to the measurement of reading motivation and achievement. A sample of 127 elementary and middle-school children aged 10 to 14 responded to measures of motivation, attributions, and achievement both longitudinally and in a challenging reading context. Novel measures of motivation and attributions were constructed, validated, and utilized to examine the relationship between ~ motivation, attributions, and achievement over a one-year period (Study I). The impact of classroom contexts and instructional practices was also explored through a study of the influence of topic interest and challenge on motivation, attributions, and persistence (Study II), as well as through interviews with children regarding motivation and reading in the classroom (Study III). Creation and validation of novel measures of motivation and attributions supported the use of a self-report measure of motivation in situation-specific contexts, and confirmed a three-factor structure of attributions for reading performance in both hypothetical and situation-specific contexts. A one-year follow up study of children's motivation and reading achievement demonstrated declines in all components of motivation beginning at age 10 through 12, and particularly strong decreases in motivation with the transition to middle school. Past perceived competence for reading predicted current achievement after controlling for past achievement, and showed the strongest relationships with reading-related skills in both elementary and middle school. Motivation and attributions were strongly related, and children with higher motivation Fulmer III displayed more adaptive attributions for reading success and failure. In the context of a developmentally inappropriate challenging reading task, children's motivation for reading, especially in terms of perceived competence, was threatened. However, interest in the story buffered some ofthe negative impacts of challenge, sustaining children's motivation, adaptive attributions, and reading persistence. Finally, children's responses during interviews outlined several emotions, perceptions, and aspects of reading tasks and contexts that influence reading motivation and achievement. Findings revealed that children with comparable motivation and achievement profiles respond in a similar way to particular reading situations, such as excessive challenge, but also that motivation is dynamic and individualistic and can change over time and across contexts. Overall, the present study outlines the importance of motivation and adaptive attributions for reading success, and the necessity of integrating various methodologies to study the dynamic construct of achievement motivation.

Multidimensional Poverty and Material Deprivation

We examine the measurement of multidimensional poverty and material deprivation following the counting approach. In contrast to earlier contributions, dimensions of well-being are not forced to be equally important but different weights can be assigned to different dimensions. We characterize a class of individual measures reflecting this feature. In addition, we axiomatize an aggregation procedure to obtain a class of indices for entire societies allowing for different degrees of inequality aversion in poverty. We apply the proposed measures to European Union member states where the concept of material deprivation was initiated.

Modelling software quality : a multidimensional approach

Les sociétés modernes dépendent de plus en plus sur les systèmes informatiques et ainsi, il y a de plus en plus de pression sur les équipes de développement pour produire des logiciels de bonne qualité. Plusieurs compagnies utilisent des modèles de qualité, des suites de programmes qui analysent et évaluent la qualité d'autres programmes, mais la construction de modèles de qualité est difficile parce qu'il existe plusieurs questions qui n'ont pas été répondues dans la littérature. Nous avons étudié les pratiques de modélisation de la qualité auprès d'une grande entreprise et avons identifié les trois dimensions où une recherche additionnelle est désirable : Le support de la subjectivité de la qualité, les techniques pour faire le suivi de la qualité lors de l'évolution des logiciels, et la composition de la qualité entre différents niveaux d'abstraction. Concernant la subjectivité, nous avons proposé l'utilisation de modèles bayésiens parce qu'ils sont capables de traiter des données ambiguës. Nous avons appliqué nos modèles au problème de la détection des défauts de conception. Dans une étude de deux logiciels libres, nous avons trouvé que notre approche est supérieure aux techniques décrites dans l'état de l'art, qui sont basées sur des règles. Pour supporter l'évolution des logiciels, nous avons considéré que les scores produits par un modèle de qualité sont des signaux qui peuvent être analysés en utilisant des techniques d'exploration de données pour identifier des patrons d'évolution de la qualité. Nous avons étudié comment les défauts de conception apparaissent et disparaissent des logiciels. Un logiciel est typiquement conçu comme une hiérarchie de composants, mais les modèles de qualité ne tiennent pas compte de cette organisation. Dans la dernière partie de la dissertation, nous présentons un modèle de qualité à deux niveaux. Ces modèles ont trois parties: un modèle au niveau du composant, un modèle qui évalue l'importance de chacun des composants, et un autre qui évalue la qualité d'un composé en combinant la qualité de ses composants. L'approche a été testée sur la prédiction de classes à fort changement à partir de la qualité des méthodes. Nous avons trouvé que nos modèles à deux niveaux permettent une meilleure identification des classes à fort changement. Pour terminer, nous avons appliqué nos modèles à deux niveaux pour l'évaluation de la navigabilité des sites web à partir de la qualité des pages. Nos modèles étaient capables de distinguer entre des sites de très bonne qualité et des sites choisis aléatoirement. Au cours de la dissertation, nous présentons non seulement des problèmes théoriques et leurs solutions, mais nous avons également mené des expériences pour démontrer les avantages et les limitations de nos solutions. Nos résultats indiquent qu'on peut espérer améliorer l'état de l'art dans les trois dimensions présentées. En particulier, notre travail sur la composition de la qualité et la modélisation de l'importance est le premier à cibler ce problème. Nous croyons que nos modèles à deux niveaux sont un point de départ intéressant pour des travaux de recherche plus approfondis.

Advances in scaling deep learning algorithms

Les algorithmes d'apprentissage profond forment un nouvel ensemble de méthodes puissantes pour l'apprentissage automatique. L'idée est de combiner des couches de facteurs latents en hierarchies. Cela requiert souvent un coût computationel plus elevé et augmente aussi le nombre de paramètres du modèle. Ainsi, l'utilisation de ces méthodes sur des problèmes à plus grande échelle demande de réduire leur coût et aussi d'améliorer leur régularisation et leur optimization. Cette thèse adresse cette question sur ces trois perspectives. Nous étudions tout d'abord le problème de réduire le coût de certains algorithmes profonds. Nous proposons deux méthodes pour entrainer des machines de Boltzmann restreintes et des auto-encodeurs débruitants sur des distributions sparses à haute dimension. Ceci est important pour l'application de ces algorithmes pour le traitement de langues naturelles. Ces deux méthodes (Dauphin et al., 2011; Dauphin and Bengio, 2013) utilisent l'échantillonage par importance pour échantilloner l'objectif de ces modèles. Nous observons que cela réduit significativement le temps d'entrainement. L'accéleration atteint 2 ordres de magnitude sur plusieurs bancs d'essai. Deuxièmement, nous introduisont un puissant régularisateur pour les méthodes profondes. Les résultats expérimentaux démontrent qu'un bon régularisateur est crucial pour obtenir de bonnes performances avec des gros réseaux (Hinton et al., 2012). Dans Rifai et al. (2011), nous proposons un nouveau régularisateur qui combine l'apprentissage non-supervisé et la propagation de tangente (Simard et al., 1992). Cette méthode exploite des principes géometriques et permit au moment de la publication d'atteindre des résultats à l'état de l'art. Finalement, nous considérons le problème d'optimiser des surfaces non-convexes à haute dimensionalité comme celle des réseaux de neurones. Tradionellement, l'abondance de minimum locaux était considéré comme la principale difficulté dans ces problèmes. Dans Dauphin et al. (2014a) nous argumentons à partir de résultats en statistique physique, de la théorie des matrices aléatoires, de la théorie des réseaux de neurones et à partir de résultats expérimentaux qu'une difficulté plus profonde provient de la prolifération de points-selle. Dans ce papier nous proposons aussi une nouvelle méthode pour l'optimisation non-convexe.