600 resultados para - Generative Fertigungsverfahren


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After years of deliberation, the EU commission sped up the reform process of a common EU digital policy considerably in 2015 by launching the EU digital single market strategy. In particular, two core initiatives of the strategy were agreed upon: General Data Protection Regulation and the Network and Information Security (NIS) Directive law texts. A new initiative was additionally launched addressing the role of online platforms. This paper focuses on the platform privacy rationale behind the data protection legislation, primarily based on the proposal for a new EU wide General Data Protection Regulation. We analyse the legislation rationale from an Information System perspective to understand the role user data plays in creating platforms that we identify as “processing silos”. Generative digital infrastructure theories are used to explain the innovative mechanisms that are thought to govern the notion of digitalization and successful business models that are affected by digitalization. We foresee continued judicial data protection challenges with the now proposed Regulation as the adoption of the “Internet of Things” continues. The findings of this paper illustrate that many of the existing issues can be addressed through legislation from a platform perspective. We conclude by proposing three modifications to the governing rationale, which would not only improve platform privacy for the data subject, but also entrepreneurial efforts in developing intelligent service platforms. The first modification is aimed at improving service differentiation on platforms by lessening the ability of incumbent global actors to lock-in the user base to their service/platform. The second modification posits limiting the current unwanted tracking ability of syndicates, by separation of authentication and data store services from any processing entity. Thirdly, we propose a change in terms of how security and data protection policies are reviewed, suggesting a third party auditing procedure.

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This chapter develops a more comprehensive theory of positive identity construction by explicating proposed mechanisms for constructing and sustaining positive individual identities. The chapter offers a broad, illustrative sampling of mechanisms for positive identity construction that are grounded in various theoretical traditions within identity scholarship. Four classical theories of identity—social identity theory, identity theory, narrative-as-identity, and identity work—offer perspectives on the impetus and mechanisms for positive identity construction. The Dutton et al. (2010) typology of positive identity is revisited to highlight those sources of positivity that each classical theory explains how to enhance. As a next step in research, positive organizational scholarship (POS) scholars and identity scholars are encouraged to examine the conditions under which increasing the positivity of an identity is associated with generative social outcomes (e.g., engaging in prosocial practices, being invested in others’ positive identity development, and deepening mutual understanding of the complex, multifaceted nature of identity).

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Thesis (Master's)--University of Washington, 2016-08

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Thesis (Ph.D.)--University of Washington, 2016-08

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Humanities Computing gave rise to the Digital Humanities, which brought considerations of a wider scope of the digital turn to humanities research. Increasingly, the area is understood to include the field of design, exemplified by definitions that describe the Digital Humanities as a “generative enterprise”. We suggest that design contributes not only to the making of digital artefacts. Design practiced with the aim to generate new knowledge constitues a research method. Design research contributes to the Digital Humanities expertise in addressing complex problems and methods for making the knowledge that is generated during a design process explicit.

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L’un des problèmes importants en apprentissage automatique est de déterminer la complexité du modèle à apprendre. Une trop grande complexité mène au surapprentissage, ce qui correspond à trouver des structures qui n’existent pas réellement dans les données, tandis qu’une trop faible complexité mène au sous-apprentissage, c’est-à-dire que l’expressivité du modèle est insuffisante pour capturer l’ensemble des structures présentes dans les données. Pour certains modèles probabilistes, la complexité du modèle se traduit par l’introduction d’une ou plusieurs variables cachées dont le rôle est d’expliquer le processus génératif des données. Il existe diverses approches permettant d’identifier le nombre approprié de variables cachées d’un modèle. Cette thèse s’intéresse aux méthodes Bayésiennes nonparamétriques permettant de déterminer le nombre de variables cachées à utiliser ainsi que leur dimensionnalité. La popularisation des statistiques Bayésiennes nonparamétriques au sein de la communauté de l’apprentissage automatique est assez récente. Leur principal attrait vient du fait qu’elles offrent des modèles hautement flexibles et dont la complexité s’ajuste proportionnellement à la quantité de données disponibles. Au cours des dernières années, la recherche sur les méthodes d’apprentissage Bayésiennes nonparamétriques a porté sur trois aspects principaux : la construction de nouveaux modèles, le développement d’algorithmes d’inférence et les applications. Cette thèse présente nos contributions à ces trois sujets de recherches dans le contexte d’apprentissage de modèles à variables cachées. Dans un premier temps, nous introduisons le Pitman-Yor process mixture of Gaussians, un modèle permettant l’apprentissage de mélanges infinis de Gaussiennes. Nous présentons aussi un algorithme d’inférence permettant de découvrir les composantes cachées du modèle que nous évaluons sur deux applications concrètes de robotique. Nos résultats démontrent que l’approche proposée surpasse en performance et en flexibilité les approches classiques d’apprentissage. Dans un deuxième temps, nous proposons l’extended cascading Indian buffet process, un modèle servant de distribution de probabilité a priori sur l’espace des graphes dirigés acycliques. Dans le contexte de réseaux Bayésien, ce prior permet d’identifier à la fois la présence de variables cachées et la structure du réseau parmi celles-ci. Un algorithme d’inférence Monte Carlo par chaîne de Markov est utilisé pour l’évaluation sur des problèmes d’identification de structures et d’estimation de densités. Dans un dernier temps, nous proposons le Indian chefs process, un modèle plus général que l’extended cascading Indian buffet process servant à l’apprentissage de graphes et d’ordres. L’avantage du nouveau modèle est qu’il admet les connections entres les variables observables et qu’il prend en compte l’ordre des variables. Nous présentons un algorithme d’inférence Monte Carlo par chaîne de Markov avec saut réversible permettant l’apprentissage conjoint de graphes et d’ordres. L’évaluation est faite sur des problèmes d’estimations de densité et de test d’indépendance. Ce modèle est le premier modèle Bayésien nonparamétrique permettant d’apprendre des réseaux Bayésiens disposant d’une structure complètement arbitraire.

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Computer games are significant since they embody our youngsters’ engagement with contemporary culture, including both play and education. These games rely heavily on visuals, systems of sign and expression based on concepts and principles of Art and Architecture. We are researching a new genre of computer games, ‘Educational Immersive Environments’ (EIEs) to provide educational materials suitable for the school classroom. Close collaboration with subject teachers is necessary, but we feel a specific need to engage with the practicing artist, the art theoretician and historian. Our EIEs are loaded with multimedia (but especially visual) signs which act to direct the learner and provide the ‘game-play’ experience forming semiotic systems. We suggest the hypothesis that computer games are a space of deconstruction and reconstruction (DeRe): When players enter the game their physical world and their culture is torn apart; they move in a semiotic system which serves to reconstruct an alternate reality where disbelief is suspended. The semiotic system draws heavily on visuals which direct the players’ interactions and produce motivating gameplay. These can establish a reconstructed culture and emerging game narrative. We have recently tested our hypothesis and have used this in developing design principles for computer game designers. Yet there are outstanding issues concerning the nature of the visuals used in computer games, and so questions for contemporary artists. Currently, the computer game industry employs artists in a ‘classical’ role in production of concept sketches, storyboards and 3D content. But this is based on a specification from the client which restricts the artist in intellectual freedom. Our DeRe hypothesis places the artist at the generative centre, to inform the game designer how art may inform our DeRe semiotic spaces. This must of course begin with the artists’ understanding of DeRe in this time when our ‘identities are becoming increasingly fractured, networked, virtualized and distributed’ We hope to persuade artists to engage with the medium of computer game technology to explore these issues. In particular, we pose several questions to the artist: (i) How can particular ‘periods’ in art history be used to inform the design of computer games? (ii) How can specific artistic elements or devices be used to design ‘signs’ to guide the player through the game? (iii) How can visual material be integrated with other semiotic strata such as text and audio?

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Teacher education researchers appear generally not well equipped to maximise a range of dissemination strategies, and remain largely separated from the policy implications of their research. How teacher education researchers address this issue and communicate their research to a wider public audience is more important than ever to consider within a global political discourse where teacher education researchers appear frustrated that their findings should, but do not, make a difference; and where the research they produce is often marginalised. This paper seeks to disrupt the widening gap between teacher education researchers and policy-makers by looking at the issue from ‘both sides’. The paper examines policy–research tensions and the critique of teacher education researchers and then outlines some of the key findings from an Australian policy-maker study. Recommendations are offered as a way for teacher education researchers to begin to mobilise a new set of generative strategies to draw from.

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One of the most challenging task underlying many hyperspectral imagery applications is the spectral unmixing, which decomposes a mixed pixel into a collection of reectance spectra, called endmember signatures, and their corresponding fractional abundances. Independent Component Analysis (ICA) have recently been proposed as a tool to unmix hyperspectral data. The basic goal of ICA is to nd a linear transformation to recover independent sources (abundance fractions) given only sensor observations that are unknown linear mixtures of the unobserved independent sources. In hyperspectral imagery the sum of abundance fractions associated to each pixel is constant due to physical constraints in the data acquisition process. Thus, sources cannot be independent. This paper address hyperspectral data source dependence and its impact on ICA performance. The study consider simulated and real data. In simulated scenarios hyperspectral observations are described by a generative model that takes into account the degradation mechanisms normally found in hyperspectral applications. We conclude that ICA does not unmix correctly all sources. This conclusion is based on the a study of the mutual information. Nevertheless, some sources might be well separated mainly if the number of sources is large and the signal-to-noise ratio (SNR) is high.

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Access to new forms, conduct and practices of educational research remain elusive providing researchers stay within the narrow theoretical constructs-the static, single vista ofconventional research models. This dissertation presents the findings of an experimental study that aims to extend the discourse of educational research through a 'performative ethnographic analysis' by using a single-site case study approach. The case study is an analytical parody based on multiple discourse relevant to a 'new' and different approach to educational research so that a more comprehensive and complex process of reading and writing text becomes possible. Throughout this process, a generative methodology and interpretative base are anticipated to provide a metaphoric focus for a critical dialogue. The discourse informing the theoretical and interpretative base of the study include philosophy, science, visual arts, literary theory, critical postructuralist theory and theatre performance. The data are presented as a series of performance narratives in the form of socio-drama, interspersed with critical reflection that enables the researcher, the research participant and reader to become part ofa triadic construct. The findings from this study have major implications for informing contemporary educational research, as they demonstrate that by approaching research in 'new' and different ways, the researcher and the educational community have access to insights that are unavailable within the constraints of conventional models ofresearch.

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With the dramatic growth of text information, there is an increasing need for powerful text mining systems that can automatically discover useful knowledge from text. Text is generally associated with all kinds of contextual information. Those contexts can be explicit, such as the time and the location where a blog article is written, and the author(s) of a biomedical publication, or implicit, such as the positive or negative sentiment that an author had when she wrote a product review; there may also be complex context such as the social network of the authors. Many applications require analysis of topic patterns over different contexts. For instance, analysis of search logs in the context of the user can reveal how we can improve the quality of a search engine by optimizing the search results according to particular users; analysis of customer reviews in the context of positive and negative sentiments can help the user summarize public opinions about a product; analysis of blogs or scientific publications in the context of a social network can facilitate discovery of more meaningful topical communities. Since context information significantly affects the choices of topics and language made by authors, in general, it is very important to incorporate it into analyzing and mining text data. In general, modeling the context in text, discovering contextual patterns of language units and topics from text, a general task which we refer to as Contextual Text Mining, has widespread applications in text mining. In this thesis, we provide a novel and systematic study of contextual text mining, which is a new paradigm of text mining treating context information as the ``first-class citizen.'' We formally define the problem of contextual text mining and its basic tasks, and propose a general framework for contextual text mining based on generative modeling of text. This conceptual framework provides general guidance on text mining problems with context information and can be instantiated into many real tasks, including the general problem of contextual topic analysis. We formally present a functional framework for contextual topic analysis, with a general contextual topic model and its various versions, which can effectively solve the text mining problems in a lot of real world applications. We further introduce general components of contextual topic analysis, by adding priors to contextual topic models to incorporate prior knowledge, regularizing contextual topic models with dependency structure of context, and postprocessing contextual patterns to extract refined patterns. The refinements on the general contextual topic model naturally lead to a variety of probabilistic models which incorporate different types of context and various assumptions and constraints. These special versions of the contextual topic model are proved effective in a variety of real applications involving topics and explicit contexts, implicit contexts, and complex contexts. We then introduce a postprocessing procedure for contextual patterns, by generating meaningful labels for multinomial context models. This method provides a general way to interpret text mining results for real users. By applying contextual text mining in the ``context'' of other text information management tasks, including ad hoc text retrieval and web search, we further prove the effectiveness of contextual text mining techniques in a quantitative way with large scale datasets. The framework of contextual text mining not only unifies many explorations of text analysis with context information, but also opens up many new possibilities for future research directions in text mining.

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Background: The male germline in flowering plants differentiates by asymmetric division of haploid uninucleated microspores, giving rise to a vegetative cell enclosing a smaller generative cell, which eventually undergoes a second mitosis to originate two sperm cells. The vegetative cell and the sperm cells activate distinct genetic and epigenetic mechanisms to control pollen tube growth and germ cell specification, respectively. Therefore, a comprehensive characterization of these processes relies on efficient methods to isolate each of the different cell types throughout male gametogenesis. Results: We developed stable transgenic Arabidopsis lines and reliable purification tools based on Fluorescence-Activated Cell Sorting (FACS) in order to isolate highly pure and viable fractions of each cell/nuclei type before and after pollen mitosis. In the case of mature pollen, this was accomplished by expressing GFP and RFP in the sperm and vegetative nuclei, respectively, resulting in 99% pure sorted populations. Microspores were also purified by FACS taking advantage of their characteristic small size and autofluorescent properties, and were confirmed to be 98% pure. Conclusions: We provide simple and efficient FACS-based purification protocols for Arabidopsis microspores, vegetative nuclei and sperm cells. This paves the way for subsequent molecular analysis such as transcriptomics, DNA methylation analysis and chromatin immunoprecipitation, in the developmental context of microgametogenesis in Arabidopsis.

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This dissertation investigates the acquisition of oblique relative clauses in L2 Spanish by English and Moroccan Arabic speakers in order to understand the role of previous linguistic knowledge and its interaction with Universal Grammar on the one hand, and the relationship between grammatical knowledge and its use in real-time, on the other hand. Three types of tasks were employed: an oral production task, an on-line self-paced grammaticality judgment task, and an on-line self-paced reading comprehension task. Results indicated that the acquisition of oblique relative clauses in Spanish is a problematic area for second language learners of intermediate proficiency in the language, regardless of their native language. In particular, this study has showed that, even when the learners’ native language shares the main properties of the L2, i.e., fronting of the obligatory preposition (Pied-Piping), there is still room for divergence, especially in production and timed grammatical intuitions. On the other hand, reaction time data have shown that L2 learners can and do converge at the level of sentence processing, showing exactly the same real-time effects for oblique relative clauses that native speakers had. Processing results demonstrated that native and non-native speakers alike are able to apply universal processing principles such as the Minimal Chain Principle (De Vincenzi, 1991) even when the L2 learners still have incomplete grammatical representations, a result that contradicts some of the predictions of the Shallow Structure Hypothesis (Clahsen & Felser, 2006). Results further suggest that the L2 processing and comprehension domains may be able to access some type of information that it is not yet available to other grammatical modules, probably because transfer of certain L1 properties occurs asymmetrically across linguistic domains. In addition, this study also explored the Null-Prep phenomenon in L2 Spanish, and proposed that Null-Prep is an interlanguage stage, fully available and accounted within UG, which intermediate L2 as well as first language learners go through in the development of pied-piping oblique relative clauses. It is hypothesized that this intermediate stage is the result of optionality of the obligatory preposition in the derivation, when it is not crucial for the meaning of the sentence, and when the DP is going to be in an A-bar position, so it can get default case. This optionality can be predicted by the Bottleneck Hypothesis (Slabakova, 2009c) if we consider that these prepositions are some sort of functional morphology. This study contributes to the field of SLA and L2 processing in various ways. First, it demonstrates that the grammatical representations may be dissociated from grammatical processing in the sense that L2 learners, unlike native speakers, can present unexpected asymmetries such as a convergent processing but divergent grammatical intuitions or production. This conclusion is only possible under the assumption of a modular language system. Finally, it contributes to the general debate of generative SLA since in argues for a fully UG-constrained interlanguage grammar.

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Why are some companies more successful than others? This thesis approaches the question by enlisting theoretical frameworks that explain the performance with internal factors, deriving from the resource-based view, namely the dynamic capabilities approach. To deepen the understanding of the drivers and barriers towards developing these higher order routines aiming at improving the operational level routines, this thesis explores the organisational culture and identity research for the microfoundational antecedents that might shed light on the formation of the dynamic capabilities. The dynamic capabilities framework in this thesis strives to take the theoretical concept closer to practical applicability. This is achieved through creation of a dynamic capabilities matrix, consisting of four dimensions often encountered in dynamic capabilities literature. The quadrants are formed along internal-external and resources-abilities axes, and consist of Sensing, Learning, Reconfiguration and Partnering facets. A key element of this thesis is the reality continuum, which illustrates the different levels of reality inherent in any entity of human individuals. The theoretical framework constructed in the thesis suggests a link between the collective but constructivist understanding of the organisation and both the operational and higher level routines, evident in the more positivist realm. The findings from three different case organisations suggest that the constructivist assumptions inherent to an organisation function as a generative base for both drivers and barriers towards developing dynamic capabilities. From each organisation one core assumption is scrutinized to identify its connections to the four dimensions of the dynamic capabilities. These connections take the form of drivers or barriers – or have the possibility to develop into one or the other. The main contribution of this thesis is to show that one key for an organisation to perform well in a turbulent setting, is to understand the different levels of realities inherent in any group of people. Recognising the intangible levels gives an advantage in the tangible ones.

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Dissertação (mestrado)—Universidade de Brasília, Instituto de Letras, Departamento de Linguística, Português e Línguas Clássicas, Programa de Pós-Graduação em Linguística, 2015.