939 resultados para Multi-Attribute Rating Technique


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The main argument developed here is the proposal of the concept of “Social Multi-Criteria Evaluation” (SMCE) as a possible useful framework for the application of social choice to the difficult policy problems of our Millennium, where, as stated by Funtowicz and Ravetz, “facts are uncertain, values in dispute, stakes high and decisions urgent”. This paper starts from the following main questions: 1. Why “Social” Multi-criteria Evaluation? 2. How such an approach should be developed? The foundations of SMCE are set up by referring to concepts coming from complex system theory and philosophy, such as reflexive complexity, post-normal science and incommensurability. To give some operational guidelines on the application of SMCE basic questions to be answered are: 1. How is it possible to deal with technical incommensurability? 2. How can we deal with the issue of social incommensurability? To answer these questions, by using theoretical considerations and lessons learned from realworld case studies, is the main objective of the present article.

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We extend the basic tax evasion model to a multi-period economy exhibiting sustained growth. When individuals conceal part of their true income from the tax authority, they face the risk of being audited and hence of paying the corresponding fine. Both taxes and fines determine individual saving and the rate of capital accumulation. In this context we show that the sign of the relation between the level of the tax rate and the amount of evaded income is the same as that obtained in static setups. Moreover, high tax rates on income are typically associated with low growth rates as occurs in standard growth models that disregard the tax evasion phenomenon.

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Estimating the social benefits of barrier-free building has always required indirect solutions, such as calculating the savings in social services, hospitalisation or adaptations made possible by the increase in accessibility. This research uses the Contingent Valuation Method to gain a direct appraisal of the benefits from barrier-free housing. When comparing two similar dwellings, with the only difference being their accessibility conditions, the 1,007 randomly chosen households that answered the direct survey would pay, on average 12.5 per cent more for being barrier-free. None of the different appraisals made on accessibility costs reaches 5 per cent. This confirms the social profitability of building without barriers and shows the potential size of the private market for those housing developers that meet the demand. Accessibility is a general concern, an economic good or attribute that most households value, irrespective of the physical conditions of their members.

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This paper presents an outline of rationale and theory of the MuSIASEM scheme (Multi-Scale Integrated Analysis of Societal and Ecosystem Metabolism). First, three points of the rationale behind our MuSIASEM scheme are discussed: (i) endosomatic and exosomatic metabolism in relation to Georgescu-Roegen’s flow-fund scheme; (2) the bioeconomic analogy of hypercycle and dissipative parts in ecosystems; (3) the dramatic reallocation of human time and land use patterns in various sectors of modern economy. Next, a flow-fund representation of the MUSIASEM scheme on three levels (the whole national level, the paid work sectors level, and the agricultural sector level) is illustrated to look at the structure of the human economy in relation to two primary factors: (i) human time - a fund; and (ii) exosomatic energy - a flow. The three levels representation uses extensive and intensive variables simultaneously. Key conceptual tools of the MuSIASEM scheme - mosaic effects and impredicative loop analysis - are explained using the three level flow-fund representation. Finally, we claim that the MuSIASEM scheme can be seen as a multi-purpose grammar useful to deal with sustainability issues.

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The goal of this paper is to study the role of multi-product firms in the market provision of product variety. The analysis is conducted using the spokes model of non-localized competition proposed by Chen and Riordan (2007). Firstly, we show that multi-product firms are at a competitive disadvantage vis-a-vis single-product firms and can only emerge if economies of scope are sufficiently strong. Secondly, under duopoly product variety may be higher or lower with respect to both the first best and the monopolistically competitive equilibrium. However, within a relevant range of parameter values duopolists drastically restrict their product range in order to relax price competition, and as a result product variety is far below the efficient level.

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Polarization indices presented up to now have only focused their attention on the distribution of income/wealth. However, in many circumstances income is not the only relevant dimension that might be the cause of social conflict, so it is very important to have a social polarization index able to cope with alternative dimensions. In this paper we present an axiomatic characterization of one of such indices: it has been obtained as an extension of the (income) polarization measure introduced in Duclos, Esteban and Ray (2004) to a wider domain. It turns out that the axiomatic structure introduced in that paper alone is not appropriate to obtain a fully satisfactory characterization of our measure, so additional axioms are proposed. As a byproduct, we present an alternative axiomatization of the aforementioned income polarization measure.

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The algorithmic approach to data modelling has developed rapidly these last years, in particular methods based on data mining and machine learning have been used in a growing number of applications. These methods follow a data-driven methodology, aiming at providing the best possible generalization and predictive abilities instead of concentrating on the properties of the data model. One of the most successful groups of such methods is known as Support Vector algorithms. Following the fruitful developments in applying Support Vector algorithms to spatial data, this paper introduces a new extension of the traditional support vector regression (SVR) algorithm. This extension allows for the simultaneous modelling of environmental data at several spatial scales. The joint influence of environmental processes presenting different patterns at different scales is here learned automatically from data, providing the optimum mixture of short and large-scale models. The method is adaptive to the spatial scale of the data. With this advantage, it can provide efficient means to model local anomalies that may typically arise in situations at an early phase of an environmental emergency. However, the proposed approach still requires some prior knowledge on the possible existence of such short-scale patterns. This is a possible limitation of the method for its implementation in early warning systems. The purpose of this paper is to present the multi-scale SVR model and to illustrate its use with an application to the mapping of Cs137 activity given the measurements taken in the region of Briansk following the Chernobyl accident.

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To study changes in survival, in biological activities and behavior of planorbids submitted to increased hydrostatic pressure, we developed a technique using two transparent chambers and a hydraulic piston. The apparatus permitted renewal of the liquid medium without substantial variations in pressure, thus eliminating excretion products and maintaining the desired O2 level and thereby permitting us to evaluate the effects of pressure independently of the occurrence of anoxia. Pressure was maintained without any contact of the liquid medium with compressed air, a situation which reproduced with relative fidelity what occurs in nature and assured the presence of the same amounts of gases in the two observation chambers (Control and Experimental). Biomphalaria glabrata was found to be able to survive at least 48 hours when submitted to 49.02 x 10**4 Pa (equivalent to a water depth of 48.8 m), continuing to day egg masses and showing few behavioral changes when compared with the control group.

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We consider a principal who deals with a privately informed agent protected by limited liability in a correlated information setting. The agent's technology is such that the fixed cost declines with the marginal cost (the type), so that countervailing incentives may arise. We show that, with high liability, the first-best outcome can be effected for any type if (1) the fixed cost is non-concave in type, under the contract that yields the smallest feasible loss to the agent; (2) the fixed cost is not very concave in type, under the contract that yields the maximum sustainable loss to the agent. We further show that, with low liability, the first-best outcome is still implemented for a non-degenerate range of types if the fixed cost is less concave in type than some given threshold, which tightens as the liability reduces. The optimal contract entails pooling otherwise.

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Este trabajo presenta un sistema para detectar y clasificar objetos binarios según la forma de éstos. En el primer paso del procedimiento, se aplica un filtrado para extraer el contorno del objeto. Con la información de los puntos de forma se obtiene un descriptor BSM con características altamente descriptivas, universales e invariantes. En la segunda fase del sistema se aprende y se clasifica la información del descriptor mediante Adaboost y Códigos Correctores de Errores. Se han usado bases de datos públicas, tanto en escala de grises como en color, para validar la implementación del sistema diseñado. Además, el sistema emplea una interfaz interactiva en la que diferentes métodos de procesamiento de imágenes pueden ser aplicados.

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In recent years, multi-atlas fusion methods have gainedsignificant attention in medical image segmentation. Inthis paper, we propose a general Markov Random Field(MRF) based framework that can perform edge-preservingsmoothing of the labels at the time of fusing the labelsitself. More specifically, we formulate the label fusionproblem with MRF-based neighborhood priors, as an energyminimization problem containing a unary data term and apairwise smoothness term. We present how the existingfusion methods like majority voting, global weightedvoting and local weighted voting methods can be reframedto profit from the proposed framework, for generatingmore accurate segmentations as well as more contiguoussegmentations by getting rid of holes and islands. Theproposed framework is evaluated for segmenting lymphnodes in 3D head and neck CT images. A comparison ofvarious fusion algorithms is also presented.

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Intraoperative cardiac imaging plays a key role during transcatheter aortic valve replacement. In recent years, new techniques and new tools for improved image quality and virtual navigation have been proposed, in order to simplify and standardize stent valve positioning and implantation. But routine performance of the new techniques may require major economic investments or specific knowledge and skills and, for this reason, they may not be accessible to the majority of cardiac centres involved in transcatheter valve replacement projects. Additionally, they still require injections of contrast medium to obtain computed images. Therefore, we have developed and describe here a very simple and intuitive method of positioning balloon-expandable stent valves, which represents the evolution of the 'dumbbell' technique for echocardiography-guided transcatheter valve replacement without angiography. This method, based on the partial inflation of the balloon catheter during positioning, traps the crimped valve in the aortic valve orifice and, consequently, very near to the ideal landing zone. It does not require specific echocardiographic knowledge; it does not require angiographies that increase the risk of postoperative kidney failure in elderly patients, and it can be also performed in centres not equipped with a hybrid operating room.