The materialist dialectical method is a philosophical investigative method to analyze aspects of reality as complex processes composed by integrating units named poles. Dialectics has experienced considerable progress in the 19th century, with Hegel's dialectics and, in the 20th century, with the works of Marx, Engels, and Gramsci, in Philosophy and Economics. The movement of poles through their contradictions is viewed as a dynamic process with intertwined phases of evolution and revolutionary crisis. Santos et al. introduced the Objective Dialectical Classifier (ODC), a non-supervised self-organized map for classification. As a case study, we used ODC to classify 181 magnetic resonance synthetic multispectral images composed by proton density, T1-and T2-weighted synthetic brain images. Comparing ODC to k-means, fuzzy c-means, and Kohonen's self-organized maps, concerning with image fidelity indexes as estimatives of quantization distortion, we proved that ODC can reach the same quantization performance as optimal non-supervised classifiers like Kohonen's self-organized maps.
Os fóruns de discussão online são um tipo de atividade reconhecidamente importante para a promoção do intercâmbio de ideias e de construção de conhecimento colaborativo no contexto do ensino online. A ativa participação de seus integrantes torna-se, portanto, um requisito fundamental para que a aprendizagem se dê efetivamente, pois uma diversidade de conhecimentos interagindo sinergicamente resulta em uma rica base para quem a consulta, e, mais ainda, pode ser absorvida de maneira profunda por quem participa de sua construção. Na educação por meio virtual, também há que se considerar a importância que vêm ganhando as técnicas de Inteligência Artificial (IA), que possibilitam a extração de informações relevantes em ambientes que geram uma grande quantidade de dados, dificilmente tratados por técnicas da computação convencional. Assim, este trabalho visa investigar como a literatura tem reportado a utilização da IA para fomentar a participação em fóruns online, utilizados na aprendizagem virtual. Uma revisão sistemática foi feita e, apesar de inicialmente ter sido retornada uma grande quantidade de resultados, após uma análise mais detalhada, foram selecionados apenas 18 trabalhos de fato relacionados com o objetivo de pesquisa. Conclui-se, deste fato, que a IA ainda não está sendo amplamente usada na resolução do problema da participação em fóruns educacionais, o que sugere uma área de estudo potencialmente subutilizada, que, se bem explorada, pode fornecer uma contribuição importante para auxiliar na eficácia desta ferramenta.
The materialist dialectical method is a philosophical investigative method to analyze aspects of reality. These aspects are viewed as complex processes composed by basic units named poles, which interact with each other. Dialectics has experienced considerable progress in the 19th century, with Hegel's dialectics and, in the 20th century, with the works of Marx, Engels, and Gramsci, in Philosophy and Economics. The movement of poles through their contradictions is viewed as a dynamic process with intertwined phases of evolution and revolutionary crisis. In order to build a computational process based on dialectics, the interaction between poles can be modeled using fuzzy membership functions.Based on this assumption, we introduce the Objective Dialectical Classifier (ODC), a non-supervised map for classification based on materialist dialectics and designed as an extension of fuzzy c-means classifier. As a case study, we used ODC to classify 181 magnetic resonance synthetic multispectral images composed by proton density, T 1 -and T 2 -weighted synthetic brain images. Comparing ODC to k-means, fuzzy c-means, and Kohonen's self-organized maps, concerning with image fidelity indexes as estimatives of quantization distortion, we proved that ODC can reach almost the same quantization performance as optimal non-supervised classifiers like Kohonen's self-organized maps.
Abstract. Providing educational resources that are able to effectively promote students' participation in a context
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