922 resultados para instances judiciaires


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This article has several interrelated goals, all of which relate to an attempt at understanding why monolingualism is taken to be the default norm in linguistic inquiry (from sociolinguistics to formal linguistic theorizing). With others, I will take the position that comparing instances of multilingualism to so-called monolingualism is an unfair and inevitably inaccurate comparison since, among other variables, the social environments and access to input of multilinguals compared to monolinguals is most often unavoidably different (cf. Cruz-Ferreira 2006; Edwards 2004). Additionally, I will attempt to demonstrate that even so-called monolinguals have access to a variety of grammars related to different registers of speech and, therefore, are not truly monolingual in the sense that they poses one monolithic grammatical competence. Taken together, the present discussion questions both the default status of monolingualism as well as the functional adequacy of the term monolingualism.

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Two aircraft instruments for the measurement of total odd nitrogen (NOy) were compared side by side aboard a Learjet A35 in April 2003 during a campaign of the AFO2000 project SPURT (Spurengastransport in der Tropopausenregion). The instruments albeit employing the same measurement principle (gold converter and chemiluminescence) had different inlet configurations. The ECO-Physics instrument operated by ETH-Zürich in SPURT had the gold converter mounted outside the aircraft, whereas the instrument operated by FZ-Jülich in the European project MOZAIC III (Measurements of ozone, water vapour, carbon monoxide and nitrogen oxides aboard Airbus A340 in-service aircraft) employed a Rosemount probe with 80 cm of FEP-tubing connecting the inlet to the gold converter. The NOy concentrations during the flight ranged between 0.3 and 3 ppb. The two data sets were compared in a blind fashion and each team followed its normal operating procedures. On average, the measurements agreed within 7%, i.e. within the combined uncertainty of the two instruments. This puts an upper limit on potential losses of HNO3 in the Rosemount inlet of the MOZAIC instrument. Larger transient deviations were observed during periods after calibrations and when the aircraft entered the stratosphere. The time lag of the MOZAIC instrument observed in these instances is in accordance with the time constant of the MOZAIC inlet line determined in the laboratory for HNO3.

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This paper explores the nature of private social and environmental reporting (SER). From interviews with UK institutional investors, we show that both investors and investees employ Goffmanesque, staged impression management as a means of creating and disseminating a dual myth of social and environmental accountability. The interviewees’ utterances unveil private meetings imbued with theatrical verbal and physical impression management. Most of the time, the investors’ shared awareness of reality belongs to a Goffmanesque frame whereby they accept no intentionality, misrepresentation or fabrication, believing instead that the ‘performers’ (investees) are not intending to deceive them. A shared perception that social and environmental considerations are subordinated to financial issues renders private SER an empty encounter characterised as a relationship-building exercise with seldom any impact on investment decision-making. Investors spoke of occasional instances of fabrication but these were insufficient to break the frame of dual myth creation. They only identified a handful of instances where intentional misrepresentation had been significant enough to alter their reality and behaviour. Only in the most extreme cases of fabrication and lying did the staged meeting break frame and become a genuine occasion of accountability, where investors demanded greater transparency, further meetings and at the extreme, divested shares. We conclude that the frontstage, ritualistic impression management in private SER is inconsistent with backstage activities within financial institutions where private financial reporting is prioritised. The investors appeared to be in a double bind whereby they devoted resources to private SER but were simultaneously aware that these efforts may be at best subordinated, at worst ignored, rendering private SER a predominantly cosmetic, theatrical and empty exercise.

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This paper offers an examination of the use(s) of the future imperative in the Latin verse inscriptions. Following introductory considerations about speech act theory, the use of directives, and politeness (with special emphasis on the Carmina Latina Epigraphica), the paper gives an overview of relevant instances. It presents an argument in favour of a (re-)interpretation of the Latin future imperative as a mode to express deontic and thetic arrangements with little immediacy. Additionally, it is possible to detect traces of a deliberate use of the future imperative as a means of marking linguistic register in contexts where it otherwise, if following a more traditional concept of the future imperative, would seem out of place

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Computational formalisms have been pushing the boundaries of the field of computing for the last 80 years and much debate has surrounded what computing entails; what it is, and what it is not. This paper seeks to explore the boundaries of the ideas of computation and provide a framework for enabling a constructive discussion of computational ideas. First, a review of computing is given, ranging from Turing Machines to interactive computing. Then, a variety of natural physical systems are considered for their computational qualities. From this exploration, a framework is presented under which all dynamical systems can be considered as instances of the class of abstract computational platforms. An abstract computational platform is defined by both its intrinsic dynamics and how it allows computation that is meaningful to an external agent through the configuration of constraints upon those dynamics. It is asserted that a platform’s computational expressiveness is directly related to the freedom with which constraints can be placed. Finally, the requirements for a formal constraint description language are considered and it is proposed that Abstract State Machines may provide a reasonable basis for such a language.

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This paper reports on a set of paleoclimate simulations for 21, 16, 14, 11 and 6 ka (thousands of years ago) carried out with the Community Climate Model, Version 1 (CCM1) of the National Center for Atmospheric Research (NCAR). This climate model uses four interactive components that were not available in our previous simulations with the NCAR CCM0 (COHMAP, 1988Science, 241, 1043–1052; Wright et al., 1993Global Climate Since the Last Glocial Maximum, University of Minnesota Press, MN): soil moisture, snow hydrology, sea-ice, and mixed-layer ocean temperature. The new simulations also use new estimates of ice sheet height and size from ( Peltier 1994, Science, 265, 195–201), and synchronize the astronomically dated orbital forcing with the ice sheet and atmospheric CO2 levels corrected from radiocarbon years to calendar years. The CCM1 simulations agree with the previous simulations in their most general characteristics. The 21 ka climate is cold and dry, in response to the presence of the ice sheets and lowered CO2 levels. The period 14–6 ka has strengthened northern summer monsoons and warm mid-latitude continental interiors in response to orbital changes. Regional differences between the CCM1 and CCM0 simulations can be traced to the effects of either the new interactive model components or the new boundary conditions. CCM1 simulates climate processes more realistically, but has additional degrees of freedom that can allow the model to ‘drift’ toward less realistic solutions in some instances. The CCM1 simulations are expressed in terms of equilibrium vegetation using BIOME 1, and indicate large shifts in biomes. Northern tundra and forest biomes are displaced southward at glacial maximum and subtropical deserts contract in the mid-Holocene when monsoons strengthen. These vegetation changes could, if simulated interactively, introduce additional climate feedbacks. The total area of vegetated land remains nearly constant through time because the exposure of continental shelves with lowered sea level largely compensates for the land covered by the expanded ice sheets.

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This contribution proposes a novel probability density function (PDF) estimation based over-sampling (PDFOS) approach for two-class imbalanced classification problems. The classical Parzen-window kernel function is adopted to estimate the PDF of the positive class. Then according to the estimated PDF, synthetic instances are generated as the additional training data. The essential concept is to re-balance the class distribution of the original imbalanced data set under the principle that synthetic data sample follows the same statistical properties. Based on the over-sampled training data, the radial basis function (RBF) classifier is constructed by applying the orthogonal forward selection procedure, in which the classifier’s structure and the parameters of RBF kernels are determined using a particle swarm optimisation algorithm based on the criterion of minimising the leave-one-out misclassification rate. The effectiveness of the proposed PDFOS approach is demonstrated by the empirical study on several imbalanced data sets.

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Automatic generation of classification rules has been an increasingly popular technique in commercial applications such as Big Data analytics, rule based expert systems and decision making systems. However, a principal problem that arises with most methods for generation of classification rules is the overfit-ting of training data. When Big Data is dealt with, this may result in the generation of a large number of complex rules. This may not only increase computational cost but also lower the accuracy in predicting further unseen instances. This has led to the necessity of developing pruning methods for the simplification of rules. In addition, classification rules are used further to make predictions after the completion of their generation. As efficiency is concerned, it is expected to find the first rule that fires as soon as possible by searching through a rule set. Thus a suit-able structure is required to represent the rule set effectively. In this chapter, the authors introduce a unified framework for construction of rule based classification systems consisting of three operations on Big Data: rule generation, rule simplification and rule representation. The authors also review some existing methods and techniques used for each of the three operations and highlight their limitations. They introduce some novel methods and techniques developed by them recently. These methods and techniques are also discussed in comparison to existing ones with respect to efficient processing of Big Data.

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The use of virtualization in high-performance computing (HPC) has been suggested as a means to provide tailored services and added functionality that many users expect from full-featured Linux cluster environments. The use of virtual machines in HPC can offer several benefits, but maintaining performance is a crucial factor. In some instances the performance criteria are placed above the isolation properties. This selective relaxation of isolation for performance is an important characteristic when considering resilience for HPC environments that employ virtualization. In this paper we consider some of the factors associated with balancing performance and isolation in configurations that employ virtual machines. In this context, we propose a classification of errors based on the concept of “error zones”, as well as a detailed analysis of the trade-offs between resilience and performance based on the level of isolation provided by virtualization solutions. Finally, a set of experiments are performed using different virtualization solutions to elucidate the discussion.

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Data on electricity consumption patterns relating to different end uses in domestic houses in Botswana is virtually non-existent, despite the fact that the total electricity consumption patterns are available. This can be attributed to the lack of measured and quantified data and in other instances the lack of modern technology to perform such investigations. This paper presents findings from initial studies that are envisaged to bridge the gap. Electricity consumption patterns of 73 domestic households across three cities have been studied. This was carried out through a questionnaire survey, calculated national metering data and electricity measurements. All together nine appliance groups were identified. The results showed the mean electricity consumption for the households considering the calculated consumption from bills and the survey to be t = 4.23; p < 0.000067, two-tailed. The findings of this paper focus on a relatively small sample size (73). It would therefore not be wise to draw sweeping conclusions from the analysis or to make statements that would be aimed at influencing policies. However, the results presented forms a formidable base for further research, which is currently on going.

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This essay will examine and compare the production of women's writing during and after the Nicaraguan and Cuban Revolutions, a corpus that includes novels, poetry, and testimonies, but also features considerable generic hybridity. Since both revolutions are separated by some twenty years, each must be understood in the context of the specific ideological conditions that framed women’s participation in culture and revolution, and must also be considered in light of evolving gender discourses, both national and international. As such, these texts respond to both local and transnational paradigms of feminine subjectivity, and highlight the particular problems that arise from women’s insertion into the revolution and its representation in literature. These writers also have to negotiate the evolving context of revolution itself, with its moments of euphoria and disenchantment – and it is here that the greatest contrasts can be found between the two revolutionary instances and their political features: whilst Cuba’s revolutionary process has somehow survived economic crisis and created a level of political stability and continuity (not without its own problems), the Nicaraguan case is characterised by ruptures and resentments which are clearly reflected in the work of writers before, during, and after the Sandinista revolution, and which continue to the present day. This chapter will address the work of the most prominent woman writer of the Nicaraguan revolution, Gioconda Belli, whose main work reflects her involvement in the Sandinista struggle; ex-commander Mónica Baltodano has recently compiled a four volume piece with testimonials of men and women who participated in the organization and actions led by the Frente Sandinista de Liberación Nacional, and Violeta Barrios de Chamorro, former president of Nicaragua, who has recently co-authored an autobiography. There are other women poets to consider, especially under the auspices of the Asociación de Mujeres Nicaraguenses Luisa Amanda Espinoza, such as Vidaluz Meneses, Michele Najlis and Daisy Zamora. The testimonios compiled by Margaret Randall are also important pieces to consider for both Nicaragua and Cuba. The most important voices of the Cuban revolution still resident on the island are poet Nancy Morejón and writers Mirta Yáñez and Aida Bahr, with younger writers such as Adelaida Fernández de Juan and Marilyn Bobes representing a more recent generation.

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The late eighties and early nineties in Germany were not only marked by the fall of the Wall and German unification, but also by the dramatization of the political issue of asylum, resulting in outbreaks of xenophobic violence. In the context of the asylum debate of the early nineties, a number of punk bands produced songs between 1991 and 1994 which criticise the xenophobic climate created by the asylum debate and undermine an exculpatory official discourse about the violent attacks. The lyrics of these songs will be analysed as instances of counter-discourse emerging from a subcultural sphere that nurtures a critical distance towards hegemonic public and political discourse, arguing that Critical Discourse Analysis should pay more attention to defiance of hegemonic discourse.

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Advances in hardware and software technologies allow to capture streaming data. The area of Data Stream Mining (DSM) is concerned with the analysis of these vast amounts of data as it is generated in real-time. Data stream classification is one of the most important DSM techniques allowing to classify previously unseen data instances. Different to traditional classifiers for static data, data stream classifiers need to adapt to concept changes (concept drift) in the stream in real-time in order to reflect the most recent concept in the data as accurately as possible. A recent addition to the data stream classifier toolbox is eRules which induces and updates a set of expressive rules that can easily be interpreted by humans. However, like most rule-based data stream classifiers, eRules exhibits a poor computational performance when confronted with continuous attributes. In this work, we propose an approach to deal with continuous data effectively and accurately in rule-based classifiers by using the Gaussian distribution as heuristic for building rule terms on continuous attributes. We show on the example of eRules that incorporating our method for continuous attributes indeed speeds up the real-time rule induction process while maintaining a similar level of accuracy compared with the original eRules classifier. We termed this new version of eRules with our approach G-eRules.

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Advances in hardware technologies allow to capture and process data in real-time and the resulting high throughput data streams require novel data mining approaches. The research area of Data Stream Mining (DSM) is developing data mining algorithms that allow us to analyse these continuous streams of data in real-time. The creation and real-time adaption of classification models from data streams is one of the most challenging DSM tasks. Current classifiers for streaming data address this problem by using incremental learning algorithms. However, even so these algorithms are fast, they are challenged by high velocity data streams, where data instances are incoming at a fast rate. This is problematic if the applications desire that there is no or only a very little delay between changes in the patterns of the stream and absorption of these patterns by the classifier. Problems of scalability to Big Data of traditional data mining algorithms for static (non streaming) datasets have been addressed through the development of parallel classifiers. However, there is very little work on the parallelisation of data stream classification techniques. In this paper we investigate K-Nearest Neighbours (KNN) as the basis for a real-time adaptive and parallel methodology for scalable data stream classification tasks.

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According to the principle of copyright exhaustion, once a copy of a work is placed on the market, the right holder’s control over further distribution of that copy is exhausted. Unlike the distribution of hard copies of copyright works, however, the electronic dissemination of content is not subject to the exhaustion principle. This means that second-hand markets of digital goods cannot exist. Traditionally, exhaustion is premised on four assumptions that cannot be safely assumed in the online context: it applies to tangible copies only; it covers goods and not services; the goods should be sold but not licensed; and the property entitlement should be alienated upon transfer. After long jurisprudential silence, courts at worldwide level have revisited these normative impediments to affirm that exhaustion can apply online in specific instances. The article discusses the doctrinal norms that underpin exhaustion and determines the conditions under which online copyright exhaustion can apply.