Análise de Agrupamentos Com Base na Teoria da Informação: Uma Abordagem Representativa

Currently, one of the biggest challenges for the field of data mining is to perform cluster analysis on complex data. Several techniques have been proposed but, in general, they can only achieve good results within specific areas providing no consensus of what would be the best way to group this kind of data. In general, these techniques fail due to non-realistic assumptions about the true probability distribution of the data. Based on this, this thesis proposes a new measure based on Cross Information Potential that uses representative points of the dataset and statistics extracted directly from data to measure the interaction between groups. The proposed approach allows us to use all advantages of this information-theoretic descriptor and solves the limitations imposed on it by its own nature. From this, two cost functions and three algorithms have been proposed to perform cluster analysis. As the use of Information Theory captures the relationship between different patterns, regardless of assumptions about the nature of this relationship, the proposed approach was able to achieve a better performance than the main algorithms in literature. These results apply to the context of synthetic data designed to test the algorithms in specific situations and to real data extracted from problems of different fields

Variação de temperatura e umidade e suas influências nas características físicas e mecânicas dos fios de algodão

Cotton is a hydrofilic textile fiber and, for this reason, it changes its properties according to the environment changes. Moisture and Temperature are the two most important factors that lead a cotton Spinning sector and influence its quality. Those two properties can change the entire Spinning process. Understanding this, moisture and temperature must be kept under control when used during the Spinning process, once the environment is hot and dry, the cotton yarns absorb moisture and lose the minimal consistency. According to this information, this paper was developed testing four types of cotton yarns, one kind of cotton from Brazil and the others from Egypt. The yarns were exposed to different temperatures and moisture in five different tests and in each test, six samples that were examined through physical and mechanical tests: resistance, strength, tenacity, yarn´s hairness, yarn´s evenness and yarn´s twisting. All the analysis were accomplished at Laboratório de Mecânica dos Fluídos and at COATS Corrente S.A., where, it was possible to use the equipments whose were fundamental to develop this paper, such as the STATIMAT ME that measures strength, tenacity, Zweigler G566, that measure hairiness in the yarn, a skein machine and a twisting machine. The analysis revealed alterations in the yarn´s characteristics in a direct way, for example, as moisture and temperature were increased, the yarn´s strength, tenacity and hairness were increased as well. Having the results of all analysis, it is possible to say that a relatively low temperature and a high humidity, cotton yarns have the best performance