90 resultados para Multidimensional DCT


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¿Cómo se podría comprometer la Comunidad Internacional, en un mundo globalizado, para la resolución de conflictos?. En el siglo XXI, pasa necesariamente por un cuestionamiento de los métodos tradicionalmente empleados para la resolución de conflictos y la seguridad (frente a nuevos escenarios nuevas estrategias). Éstas toman forma en las doctrinas de la prevención, transformación, resolución de conflictos, gestión de crisis, y seguridad multidimensional/colectiva. Trasladándolo a Europa, la implantación de políticas comunes en las zonas en conflicto, urge cada día más. No existe una acción exterior colectiva ante el estallido de una crisis, porque al final siempre acaban prevaleciendo las decisiones de los Estados más poderosos. Es este mismo proceso decisional, anclado en las posturas realistas, el que bloquea o retarda todo intento de reacción común. Mientras, la violencia se sucede y asistimos impotentes a escenarios bélicos o escaladas, bajo la mirada atrapada de Occidente. La UE se enfrenta a un desafío cada vez más presente, por conseguir una acción globalizadora en materia de derechos humanos, porque frente a la globalización económica surge la necesidad de contrarestar sus efectos, globalizando también los derechos humanos. Cabría revisar las respuestas y capacidades europeas ante el estallido de una crisis.

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This document contains a report and summary of the field research activities in a rural community of rice farmers in Kampot province, Cambodia in 2011, which I conducted within the context of my PhD research at ICTA-UAB (Institute of Environmental Science and Technology, Autonomous University of Barcelona, Spain). The purpose of the field research was to gather data for a MuSIASEM analysis (Multi-Scale Integrated Analysis of Societal and Ecosystem Metabolism) at the village and household level, in order to analyze the multidimensional challenges that small farmers may face nowadays within the context of global rural change and declining access to land. While the literature on MuSIASEM offers a great variety of theoretical explanations and practical applications, there is little information available for students regarding the practical steps required for doing a MuSIASEM analysis at the local level. Within this context, this report offers not only a documentation of the field research design and data collection methods, but further provides a general overview on some organizational and preparative aspects, including some personal reflections, that one may face when preparing and conducting field research for MuSIASEM analysis. In summary, this document thus serves three objectives: (i) to assure methodological transparency for the future work, based on the collected data during field research, (ii) to share my personal experience on the preparative and practical steps required for field research and data collection for a MuSIASEM analysis at the local level, and (iii) to make available for the further interested reader some more detailed background information on the case study village.

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In the last decades; a growing stock of literature has been devoted to the criticism of GDP as an indicator of societal wealth. A relevant question is: what are the perspectives to build, on the existing knowledge and consensus, alternative measures of prosperity? A starting point may be to connect well-being research agenda with the sustainability one. However, there is no doubt that there is a lot of complexity and fuzziness inherent in multidimensional concepts such as sustainability and well-being. This article analyses the theoretical foundations and the empirical validity of some multidimensional technical tools that can be used for well-being evaluation and assessment. Of course one should not forget that policy conclusions derived through any mathematical model depend also on the conceptual framework used, i.e. which representation of reality (and thus which societal values and interests) has been considered.

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When one wishes to implement public policies, there is a previous need of comparing different actions and valuating and evaluating them to assess their social attractiveness. Recently the concept of well-being has been proposed as a multidimensional proxy for measuring societal prosperity and progress; a key research topic is then on how we can measure and evaluate this plurality of dimensions for policy decisions. This paper defends the thesis articulated in the following points: 1. Different metrics are linked to different objectives and values. To use only one measurement unit (on the grounds of the so-called commensurability principle) for incorporating a plurality of dimensions, objectives and values, implies reductionism necessarily. 2. Point 1) can be proven as a matter of formal logic by drawing on the work of Geach about moral philosophy. This theoretical demonstration is an original contribution of this article. Here the distinction between predicative and attributive adjectives is formalised and definitions are provided. Predicative adjectives are further distinguished into absolute and relative ones. The new concepts of set commensurability and rod commensurability are introduced too. 3. The existence of a plurality of social actors, with interest in the policy being assessed, causes that social decisions involve multiple types of values, of which economic efficiency is only one. Therefore it is misleading to make social decisions based only on that one value. 4. Weak comparability of values, which is grounded on incommensurability, is proved to be the main methodological foundation of policy evaluation in the framework of well-being economics. Incommensurability does not imply incomparability; on the contrary incommensurability is the only rational way to compare societal options under a plurality of policy objectives. 5. Weak comparability can be implemented by using multi-criteria evaluation, which is a formal framework for applied consequentialism under incommensurability. Social Multi-Criteria Evaluation, in particular, allows considering both technical and social incommensurabilities simultaneously.

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Background: Despite the fact that labour market flexibility has resulted in an expansion of precarious employment in industrialized countries, to date there is limited empirical evidence about its health consequences. The Employment Precariousness Scale (EPRES) is a newly developed, theory-based, multidimensional questionnaire specifically devised for epidemiological studies among waged and salaried workers. Objective: To assess acceptability, reliability and construct validity of EPRES in a sample of waged and salaried workers in Spain. Methods: Cross-sectional study, using a sub-sample of 6.968 temporary and permanent workers from a population-based survey carried out in 2004-2005. The survey questionnaire was interviewer administered and included the six EPRES subscales, measures of the psychosocial work environment (COPSOQ ISTAS21), and perceived general and mental health (SF-36). Results: A high response rate to all EPRES items indicated good acceptability; Cronbach’s alpha coefficients, over 0.70 for all subscales and the global score, demonstrated good internal consistency reliability; exploratory factor analysis using principal axis analysis and varimax rotation confirmed the six-subscale structure and the theoretical allocation of all items. Patterns across known groups and correlation coefficients with psychosocial work environment measures and perceived health demonstrated the expected relations, providing evidence of construct validity. Conclusions: Our results provide evidence in support of the psychometric properties of EPRES, which appears to be a promising tool for the measurement of employment precariousness in public health research.

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We present a new technique for audio signal comparison based on tonal subsequence alignment and its application to detect cover versions (i.e., different performances of the same underlying musical piece). Cover song identification is a task whose popularity has increased in the Music Information Retrieval (MIR) community along in the past, as it provides a direct and objective way to evaluate music similarity algorithms.This article first presents a series of experiments carried outwith two state-of-the-art methods for cover song identification.We have studied several components of these (such as chroma resolution and similarity, transposition, beat tracking or Dynamic Time Warping constraints), in order to discover which characteristics would be desirable for a competitive cover song identifier. After analyzing many cross-validated results, the importance of these characteristics is discussed, and the best-performing ones are finally applied to the newly proposed method. Multipleevaluations of this one confirm a large increase in identificationaccuracy when comparing it with alternative state-of-the-artapproaches.

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In this article, we present the current state of our work on a linguistically-motivated model for automatic summarization of medical articles in Spanish. The model takes into account the results of an empirical study which reveals that, on the one hand, domain-specific summarization criteria can often be derived from the summaries of domain specialists, and, on the other hand, adequate summarization strategies must be multidimensional, i.e., cover various types of linguistic clues. We take into account the textual, lexical, discursive, syntactic and communicative dimensions. This is novel in the field of summarization. The experiments carried out so far indicate that our model is suitable to provide high quality summarizations.

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Silver Code (SilC) was originally discovered in [1–4] for 2×2 multiple-input multiple-output (MIMO) transmission. It has non-vanishing minimum determinant 1/7, slightly lower than Golden code, but is fast-decodable, i.e., it allows reduced-complexity maximum likelihood decoding [5–7]. In this paper, we present a multidimensional trellis-coded modulation scheme for MIMO systems [11] based on set partitioning of the Silver Code, named Silver Space-Time Trellis Coded Modulation (SST-TCM). This lattice set partitioning is designed specifically to increase the minimum determinant. The branches of the outer trellis code are labeled with these partitions. Viterbi algorithm is applied for trellis decoding, while the branch metrics are computed by using a sphere-decoding algorithm. It is shown that the proposed SST-TCM performs very closely to the Golden Space-Time Trellis Coded Modulation (GST-TCM) scheme, yetwith a much reduced decoding complexity thanks to its fast-decoding property.

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Graphical displays which show inter--sample distances are importantfor the interpretation and presentation of multivariate data. Except whenthe displays are two--dimensional, however, they are often difficult tovisualize as a whole. A device, based on multidimensional unfolding, isdescribed for presenting some intrinsically high--dimensional displays infewer, usually two, dimensions. This goal is achieved by representing eachsample by a pair of points, say $R_i$ and $r_i$, so that a theoreticaldistance between the $i$-th and $j$-th samples is represented twice, onceby the distance between $R_i$ and $r_j$ and once by the distance between$R_j$ and $r_i$. Self--distances between $R_i$ and $r_i$ need not be zero.The mathematical conditions for unfolding to exhibit symmetry are established.Algorithms for finding approximate fits, not constrained to be symmetric,are discussed and some examples are given.

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This paper studies the relationship between the amount of publicinformation that stock market prices incorporate and the equilibriumbehavior of market participants. The analysis is framed in a static, NREEsetup where traders exchange vectors of assets accessing multidimensionalinformation under two alternative market structures. In the first(the unrestricted system), both informed and uninformed speculators cancondition their demands for each traded asset on all equilibrium prices;in the second (the restricted system), they are restricted to conditiontheir demand on the price of the asset they want to trade. I show thatinformed traders incentives to exploit multidimensional privateinformation depend on the number of prices they can condition upon whensubmitting their demand schedules, and on the specific price formationprocess one considers. Building on this insight, I then give conditionsunder which the restricted system is more efficient than the unrestrictedsystem.

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Perceptual maps have been used for decades by market researchers to illuminatethem about the similarity between brands in terms of a set of attributes, to position consumersrelative to brands in terms of their preferences, or to study how demographic and psychometricvariables relate to consumer choice. Invariably these maps are two-dimensional and static. Aswe enter the era of electronic publishing, the possibilities for dynamic graphics are opening up.We demonstrate the usefulness of introducing motion into perceptual maps through fourexamples. The first example shows how a perceptual map can be viewed in three dimensions,and the second one moves between two analyses of the data that were collected according todifferent protocols. In a third example we move from the best view of the data at the individuallevel to one which focuses on between-group differences in aggregated data. A final exampleconsiders the case when several demographic variables or market segments are available foreach respondent, showing an animation with increasingly detailed demographic comparisons.These examples of dynamic maps use several data sets from marketing and social scienceresearch.

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Principal curves have been defined Hastie and Stuetzle (JASA, 1989) assmooth curves passing through the middle of a multidimensional dataset. They are nonlinear generalizations of the first principalcomponent, a characterization of which is the basis for the principalcurves definition.In this paper we propose an alternative approach based on a differentproperty of principal components. Consider a point in the space wherea multivariate normal is defined and, for each hyperplane containingthat point, compute the total variance of the normal distributionconditioned to belong to that hyperplane. Choose now the hyperplaneminimizing this conditional total variance and look for thecorresponding conditional mean. The first principal component of theoriginal distribution passes by this conditional mean and it isorthogonal to that hyperplane. This property is easily generalized todata sets with nonlinear structure. Repeating the search from differentstarting points, many points analogous to conditional means are found.We call them principal oriented points. When a one-dimensional curveruns the set of these special points it is called principal curve oforiented points. Successive principal curves are recursively definedfrom a generalization of the total variance.

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Subcompositional coherence is a fundamental property of Aitchison s approach to compositional data analysis, and is the principal justification for using ratios of components. We maintain, however, that lack of subcompositional coherence, that is incoherence, can be measured in an attempt to evaluate whether any given technique is close enough, for all practical purposes, to being subcompositionally coherent. This opens up the field to alternative methods, which might be better suited to cope with problems such as data zeros and outliers, while being only slightly incoherent. The measure that we propose is based on the distance measure between components. We show that the two-part subcompositions, which appear to be the most sensitive to subcompositional incoherence, can be used to establish a distance matrix which can be directly compared with the pairwise distances in the full composition. The closeness of these two matrices can be quantified using a stress measure that is common in multidimensional scaling, providing a measure of subcompositional incoherence. The approach is illustrated using power-transformed correspondence analysis, which has already been shown to converge to log-ratio analysis as the power transform tends to zero.

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We construct a weighted Euclidean distance that approximates any distance or dissimilarity measure between individuals that is based on a rectangular cases-by-variables data matrix. In contrast to regular multidimensional scaling methods for dissimilarity data, the method leads to biplots of individuals and variables while preserving all the good properties of dimension-reduction methods that are based on the singular-value decomposition. The main benefits are the decomposition of variance into components along principal axes, which provide the numerical diagnostics known as contributions, and the estimation of nonnegative weights for each variable. The idea is inspired by the distance functions used in correspondence analysis and in principal component analysis of standardized data, where the normalizations inherent in the distances can be considered as differential weighting of the variables. In weighted Euclidean biplots we allow these weights to be unknown parameters, which are estimated from the data to maximize the fit to the chosen distances or dissimilarities. These weights are estimated using a majorization algorithm. Once this extra weight-estimation step is accomplished, the procedure follows the classical path in decomposing the matrix and displaying its rows and columns in biplots.

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Las exacerbaciones de la enfermedad pulmonar obstructiva crónica (EA-EPOC) constituyen una de las principales causas de hospitalización y de asistencia a los Servicios de Urgencias, lo cual les confiere ser las responsables de una gran carga sobre el sistema sanitario. En nuestro estudio hemos evaluado el impacto de un modo asistencial alternativo (los hospitales de día de enfermedades respiratorias -HDER-) sobre la tasa de ingresos durante las EA-EPOC. Los resultados muestran que la atención en los HDER puede disminuir el número de ingresos en comparación con los Servicios de Urgencias a partir de un modelo de atención continuada y multidimensional.