919 resultados para generative Verfahren


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This paper discusses the development of a new Bachelor of Education (Middle Years of Schooling) at The University of Queensland. The middle years of schooling have increasingly been the focus of education reform initiatives in Australia, but this has not been accompanied by significant increases in the number of teacher education institutions offering specialised middle schooling-level teacher preparation programmes. Considering the rapidly changing social and economic context and the emergent state of middle schooling in Australia, the programme represented a conceptual and practical opportunity and challenge for The University of Queensland team. Working collaboratively, the team sought to design a teacher education preservice programme that was both responsive and generative: that is, responsive to local school contexts and to current educational research and reform at national and international levels; and generative of cutting-edge theories and practices associated with middle schooling, teachers' work, and teacher education. This paper focuses on one component of the Middle Years of Schooling Teacher Education programme at The University of Queensland; namely, the practicum. We first present the underlying principles of the practicum programme and then examine "dilemmas" that emerged early in the practicum. These issues and tensions were associated with the ideals of "middle years" philosophy and the pragmatics of school reform associated with that new approach. In this paper, and within this context, we explore what it means to be both responsive and generative, and describe how we as teacher educators negotiated between the extremes these terms implied.

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Esta pesquisa analisou a resistência ao currículo de História para o ensino médio prescrito pela Secretaria de Estado da Educação do Estado do Espírito Santo (Sedu) em 2009, para ser desenvolvido em sua rede de ensino pelos professores dessa etapa da educação básica. Seu objetivo foi investigar as causas de resistências assentadas ao documento e identificar a que os professores resistem, por que os professores resistem e como os professores estão materializando sua resistência a ele. Por resistência entende-se o conjunto de práticas exercidas pelos professores que se anunciam sob a forma de oposição, na tentativa de barrar a dominação, de não perder sua identidade. Uma resistência consciente que, apesar de rejeitar, não nega o currículo. Porém, a ele não se submete passivamente, numa posição de quem reivindica sua reelaboração, sua reinvenção. Para fundamentação teórica, ocorreram pesquisas e estudos de produções e conceitos sobre currículo, resistência, ensino médio e suas relações com a educação. O trabalho encontra-se na área de educação, na linha de pesquisa Cultura, Currículo e Formação de Educadores. A pesquisa é de cunho qualitativo e amparou-se na abordagem narrativa. Como procedimentos metodológicos, apoiou-se na análise documental e bibliográfica, questionário pré-estruturado, observações e conversas com quatro professoras de História de ensino médio no município de Afonso Cláudio, Estado do Espírito Santo. Com o cotejamento dos dados produzidos, o pressuposto apresentado neste trabalho foi confirmado. Como dimensões geradoras de resistências, ficaram evidenciadas a prescrição, considerando que as professoras ajuízam ser essa uma atribuição delas, junto com a escola; a organização dos conteúdos apresentada pela Sedu; a ausência de linearidade dos acontecimentos históricos; a disposição dos saberes por eixos temáticos; a orientação pelo trabalho interdisciplinar; a desvinculação dos conteúdos de cada série/ano do livro didático; a exigência burocrática com a implantação do currículo. A contribuição do trabalho para a Rede Estadual de Ensino foi a problematização da resistência ao currículo, artefato educacional que pode produzir estabilidades ou tensões entre os sujeitos que o envolvem, podendo ser útil para discussões posteriores. Para as educadoras, o trabalho foi relevante por ter promovido espaço de debates sobre o currículo de História do ensino médio no decurso das conversas na escola.

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It is proposed a new approach based on a methodology, assisted by a tool, to create new products in the automobile industry based on previous defined processes and experiences inspired on a set of best practices or principles: it is based on high-level models or specifications; it is component-based architecture centric; it is based on generative programming techniques. This approach follows in essence the MDA (Model Driven Architecture) philosophy with some specific characteristics. We propose a repository that keeps related information, such as models, applications, design information, generated artifacts and even information concerning the development process itself (e.g., generation steps, tests and integration milestones). Generically, this methodology receives the users' requirements to a new product (e.g., functional, non-functional, product specification) as its main inputs and produces a set of artifacts (e.g., design parts, process validation output) as its main output, that will be integrated in the engineer design tool (e.g. CAD system) facilitating the work.

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Notre objectif consiste à interroger les effets de dispositifs d’enseignement apprentissage de l’écriture narrative, en prenant pour analyseur l’usage du stéréotype par des élèves de la fin de l’école élémentaire. Le stéréotype, considéré comme le lieu commun de l’expression (Dufays & Kervin, 2010) est potentiellement générateur de ressources (Marin & Crinon, 2014, à paraître) par les contraintes mêmes qu’il induit (Plane, 2006). En prise sur l’appréhension des critères de genre, la reconnaissance des stéréotypes renvoie à une forme particulièrement discriminante de capital symbolique (Tardy et Swales, 2008) dont il convient d’envisager les effets sur la régulation des inégalités entre élèves (Rochex & Crinon, 2011). Nous présentons en complémentarité deux recherches, dans lesquelles les élèves bénéficient de ressources de nature différente : l’aide apportée y assumant pour la première le statut d’outil technique (Crinon, Legros & Marin, 2002-2003), alors qu’elle relève pour la seconde d’un instrument psychologique (Marin, 2011). Les résultats de ces recherches montrent comment la focalisation sur les critères de genre constitue une ressource utile aux élèves, la seconde mettant en exergue le rôle des tuteurs dans la critique des textes de leurs pairs et son effet récursif sur la conscientisation des invariants génériques du texte de fiction.

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The development of high spatial resolution airborne and spaceborne sensors has improved the capability of ground-based data collection in the fields of agriculture, geography, geology, mineral identification, detection [2, 3], and classification [4–8]. The signal read by the sensor from a given spatial element of resolution and at a given spectral band is a mixing of components originated by the constituent substances, termed endmembers, located at that element of resolution. This chapter addresses hyperspectral unmixing, which is the decomposition of the pixel spectra into a collection of constituent spectra, or spectral signatures, and their corresponding fractional abundances indicating the proportion of each endmember present in the pixel [9, 10]. Depending on the mixing scales at each pixel, the observed mixture is either linear or nonlinear [11, 12]. The linear mixing model holds when the mixing scale is macroscopic [13]. The nonlinear model holds when the mixing scale is microscopic (i.e., intimate mixtures) [14, 15]. The linear model assumes negligible interaction among distinct endmembers [16, 17]. The nonlinear model assumes that incident solar radiation is scattered by the scene through multiple bounces involving several endmembers [18]. Under the linear mixing model and assuming that the number of endmembers and their spectral signatures are known, hyperspectral unmixing is a linear problem, which can be addressed, for example, under the maximum likelihood setup [19], the constrained least-squares approach [20], the spectral signature matching [21], the spectral angle mapper [22], and the subspace projection methods [20, 23, 24]. Orthogonal subspace projection [23] reduces the data dimensionality, suppresses undesired spectral signatures, and detects the presence of a spectral signature of interest. The basic concept is to project each pixel onto a subspace that is orthogonal to the undesired signatures. As shown in Settle [19], the orthogonal subspace projection technique is equivalent to the maximum likelihood estimator. This projection technique was extended by three unconstrained least-squares approaches [24] (signature space orthogonal projection, oblique subspace projection, target signature space orthogonal projection). Other works using maximum a posteriori probability (MAP) framework [25] and projection pursuit [26, 27] have also been applied to hyperspectral data. In most cases the number of endmembers and their signatures are not known. Independent component analysis (ICA) is an unsupervised source separation process that has been applied with success to blind source separation, to feature extraction, and to unsupervised recognition [28, 29]. ICA consists in finding a linear decomposition of observed data yielding statistically independent components. Given that hyperspectral data are, in given circumstances, linear mixtures, ICA comes to mind as a possible tool to unmix this class of data. In fact, the application of ICA to hyperspectral data has been proposed in reference 30, where endmember signatures are treated as sources and the mixing matrix is composed by the abundance fractions, and in references 9, 25, and 31–38, where sources are the abundance fractions of each endmember. In the first approach, we face two problems: (1) The number of samples are limited to the number of channels and (2) the process of pixel selection, playing the role of mixed sources, is not straightforward. In the second approach, ICA is based on the assumption of mutually independent sources, which is not the case of hyperspectral data, since the sum of the abundance fractions is constant, implying dependence among abundances. This dependence compromises ICA applicability to hyperspectral images. In addition, hyperspectral data are immersed in noise, which degrades the ICA performance. IFA [39] was introduced as a method for recovering independent hidden sources from their observed noisy mixtures. IFA implements two steps. First, source densities and noise covariance are estimated from the observed data by maximum likelihood. Second, sources are reconstructed by an optimal nonlinear estimator. Although IFA is a well-suited technique to unmix independent sources under noisy observations, the dependence among abundance fractions in hyperspectral imagery compromises, as in the ICA case, the IFA performance. Considering the linear mixing model, hyperspectral observations are in a simplex whose vertices correspond to the endmembers. Several approaches [40–43] have exploited this geometric feature of hyperspectral mixtures [42]. Minimum volume transform (MVT) algorithm [43] determines the simplex of minimum volume containing the data. The MVT-type approaches are complex from the computational point of view. Usually, these algorithms first find the convex hull defined by the observed data and then fit a minimum volume simplex to it. Aiming at a lower computational complexity, some algorithms such as the vertex component analysis (VCA) [44], the pixel purity index (PPI) [42], and the N-FINDR [45] still find the minimum volume simplex containing the data cloud, but they assume the presence in the data of at least one pure pixel of each endmember. This is a strong requisite that may not hold in some data sets. In any case, these algorithms find the set of most pure pixels in the data. Hyperspectral sensors collects spatial images over many narrow contiguous bands, yielding large amounts of data. For this reason, very often, the processing of hyperspectral data, included unmixing, is preceded by a dimensionality reduction step to reduce computational complexity and to improve the signal-to-noise ratio (SNR). Principal component analysis (PCA) [46], maximum noise fraction (MNF) [47], and singular value decomposition (SVD) [48] are three well-known projection techniques widely used in remote sensing in general and in unmixing in particular. The newly introduced method [49] exploits the structure of hyperspectral mixtures, namely the fact that spectral vectors are nonnegative. The computational complexity associated with these techniques is an obstacle to real-time implementations. To overcome this problem, band selection [50] and non-statistical [51] algorithms have been introduced. This chapter addresses hyperspectral data source dependence and its impact on ICA and IFA performances. The study consider simulated and real data and is based on mutual information minimization. Hyperspectral observations are described by a generative model. This model takes into account the degradation mechanisms normally found in hyperspectral applications—namely, signature variability [52–54], abundance constraints, topography modulation, and system noise. The computation of mutual information is based on fitting mixtures of Gaussians (MOG) to data. The MOG parameters (number of components, means, covariances, and weights) are inferred using the minimum description length (MDL) based algorithm [55]. We study the behavior of the mutual information as a function of the unmixing matrix. The conclusion is that the unmixing matrix minimizing the mutual information might be very far from the true one. Nevertheless, some abundance fractions might be well separated, mainly in the presence of strong signature variability, a large number of endmembers, and high SNR. We end this chapter by sketching a new methodology to blindly unmix hyperspectral data, where abundance fractions are modeled as a mixture of Dirichlet sources. This model enforces positivity and constant sum sources (full additivity) constraints. The mixing matrix is inferred by an expectation-maximization (EM)-type algorithm. This approach is in the vein of references 39 and 56, replacing independent sources represented by MOG with mixture of Dirichlet sources. Compared with the geometric-based approaches, the advantage of this model is that there is no need to have pure pixels in the observations. The chapter is organized as follows. Section 6.2 presents a spectral radiance model and formulates the spectral unmixing as a linear problem accounting for abundance constraints, signature variability, topography modulation, and system noise. Section 6.3 presents a brief resume of ICA and IFA algorithms. Section 6.4 illustrates the performance of IFA and of some well-known ICA algorithms with experimental data. Section 6.5 studies the ICA and IFA limitations in unmixing hyperspectral data. Section 6.6 presents results of ICA based on real data. Section 6.7 describes the new blind unmixing scheme and some illustrative examples. Section 6.8 concludes with some remarks.

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Dissertação para obtenção do Grau de Mestre em Engenharia Informática

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“In the midst of order, there is chaos; but in the midst of chaos, there is order”, John Gribbin wrote in his book Deep Simplicity (p.76). In this dialectical spirit, we discuss the generative tension between complexity and simplicity in the theory and practice of management and organization. Complexity theory suggests that the relationship between complex environments and complex organizations advanced by the well-known Ashby’s law, may be reconsidered: only simple organization provides enough space for individual agency to match environmental turbulence in the form of complex organizational responses. We suggest that complex organizing may be paradoxically facilitated by a simple infrastructure, and that the theory of organizations may be viewed as resulting from the interplay between simplicity and complexity.

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Search is now going beyond looking for factual information, and people wish to search for the opinions of others to help them in their own decision-making. Sentiment expressions or opinion expressions are used by users to express their opinion and embody important pieces of information, particularly in online commerce. The main problem that the present dissertation addresses is how to model text to find meaningful words that express a sentiment. In this context, I investigate the viability of automatically generating a sentiment lexicon for opinion retrieval and sentiment classification applications. For this research objective we propose to capture sentiment words that are derived from online users’ reviews. In this approach, we tackle a major challenge in sentiment analysis which is the detection of words that express subjective preference and domain-specific sentiment words such as jargon. To this aim we present a fully generative method that automatically learns a domain-specific lexicon and is fully independent of external sources. Sentiment lexicons can be applied in a broad set of applications, however popular recommendation algorithms have somehow been disconnected from sentiment analysis. Therefore, we present a study that explores the viability of applying sentiment analysis techniques to infer ratings in a recommendation algorithm. Furthermore, entities’ reputation is intrinsically associated with sentiment words that have a positive or negative relation with those entities. Hence, is provided a study that observes the viability of using a domain-specific lexicon to compute entities reputation. Finally, a recommendation system algorithm is improved with the use of sentiment-based ratings and entities reputation.

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Multiphase flows, hyperbolic model, Godunov method, nozzle flow, nonstrictly hyperbolic

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Electrochromatography, numerical simulation, electrokinetics, electroosmosis, parallel computing

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Aufgrund der Entwicklungen auf dem Sektor der Mobiletelefone ist davon auszugehen, dass die Anzahl kleiner, leichtgewichtiger mobiler Endgeräte, welche als Clients von Datenbanksystemen genutzt werden, weiter ansteigt. Ein wesentliches Problem in diesem Szenario ist die langsame und teure Datenübertragung in Funknetzwerken. Aus Sicht der Nutzer derartiger Technologien ist es somit nicht sinnvoll bzw. wünschenswert, Daten, welche keinen direkten Nutzen für sie bieten, auf das Mobilgerät zu übertragen. Des Weiteren werden einmal empfangene Daten lokal gespeichert und wiederverwendet (Caching). Ändern sich Daten auf dem Server des Informationssystems, müssen die mobilen Clients, welche von einer Änderung betroffen sind, ermittelt und darüber informiert werden. Im Rahmen dieser Dissertation wird gezeigt, dass eine derartige exakte Relevanzprüfung nur mithilfe der Daten in der Datenbank realisiert werden kann. Andere Verfahren, welche das Problem auf semantischer Ebene adressieren, funktionieren nur, wenn die unterstützte Anfragesprache stark eingeschränkt wird und können selbst dann zur falschen Feststellung einer Relevanz führen. Insbesonderen in Informationssystemen mit einer großen Anzahl mobiler Clients kommt es dazu, dass verschiedene Nutzer gleiche oder zumindest ähnliche Anfragen stellen. Diese Eigenschaft wird hier genutzt, um basierend auf einer speziellen Anfragenotation syntaktisch gleiche Teile mehrerer Anfragen gemeinsam auf Relevanz zu testen. Hierzu werden die Anfragen in einem Anfragebaum gespeichert, welcher die IDs der Clients referenziert. Die Relevanzprüfung erfolgt durch Traversieren des Baumes. In der vorliegenden Arbeit werden verschiedene Anfrageindexstrukturen diskutiert und die Menge der notwendigen Relevanztest formal auf der Basis der Relationenmodells hergeleitet. Abschließend werden die theoretisch erarbeiteten Techniken evaluiert und Vorschläge für ihre Optimierung diskutiert.

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Multiproduct plants, Dynamic Optimization, Mixed Integer Linear/Non-Linear Programming, Scheduling

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Fluidized beds, granulation, heat and mass transfer, calcium dynamics, stochastic process, finite element methods, Rosenbrock methods, multigrid methods, parallelization

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Biosignals processing, Biological Nonlinear and time-varying systems identification, Electomyograph signals recognition, Pattern classification, Fuzzy logic and neural networks methods