3 resultados para Societies, Medical

em Archivo Digital para la Docencia y la Investigación - Repositorio Institucional de la Universidad del País Vasco


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This chapter studies multilingual democratic societies with highly developed economies. These societies are assumed to have two languages with official status: language A, spoken by every individual, and language B, spoken by the bilingual minority. We emphasize that language rights are important, but the survival of the minority language B depends mainly on the actual use bilinguals make of B. The purpose of the present chapter is to study some of the factors affecting the bilingual speakers language choice behaviour. Our view is that languages with their speech communities compete for speakers just as fi rms compete for market share. Thus, the con ict among the minority languages in these societies does not take the rough expressions such as those studied in Desmet et al. (2012). Here the con flict is more subtle. We model highly plausible language choice situations by means of choice procedures and non-cooperative games, each with different types of information. We then study the determinants of the bilinguals ' strategic behaviour with regard to language. We observe that the bilinguals' use of B is shaped, essentially, by linguistic conventions and social norms that are developed in situations of language contact.

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My project is a business plan about the set up of a company and the development of a new and innovative product aimed for the elders. I decide do this project when I discover that one of the more important needs that have the elders is to remember the medicines that they have to take. I thought that a good way could be through a smart watch. My watch have an only function, is a cheap device, easy to use, easy to understand and easy to set up, because the elders usually do not know to use complex electronics devices. There are other similar smart watches and other devices but do not have the necessary characteristics to be a good reminder for elders. My watch is centred to improve the life of the elders, but my product could also be useful for ill people who have to take many medicines during the day. After realizing this business plan, I have proved that my company is viable in the environment and profitable in the market.

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In the problem of one-class classification (OCC) one of the classes, the target class, has to be distinguished from all other possible objects, considered as nontargets. In many biomedical problems this situation arises, for example, in diagnosis, image based tumor recognition or analysis of electrocardiogram data. In this paper an approach to OCC based on a typicality test is experimentally compared with reference state-of-the-art OCC techniques-Gaussian, mixture of Gaussians, naive Parzen, Parzen, and support vector data description-using biomedical data sets. We evaluate the ability of the procedures using twelve experimental data sets with not necessarily continuous data. As there are few benchmark data sets for one-class classification, all data sets considered in the evaluation have multiple classes. Each class in turn is considered as the target class and the units in the other classes are considered as new units to be classified. The results of the comparison show the good performance of the typicality approach, which is available for high dimensional data; it is worth mentioning that it can be used for any kind of data (continuous, discrete, or nominal), whereas state-of-the-art approaches application is not straightforward when nominal variables are present.