47 resultados para Incremental mining


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The increase in new electronic devices had generated a considerable increase in obtaining spatial data information; hence these data are becoming more and more widely used. As well as for conventional data, spatial data need to be analyzed so interesting information can be retrieved from them. Therefore, data clustering techniques can be used to extract clusters of a set of spatial data. However, current approaches do not consider the implicit semantics that exist between a region and an object’s attributes. This paper presents an approach that enhances spatial data mining process, so they can use the semantic that exists within a region. A framework was developed, OntoSDM, which enables spatial data mining algorithms to communicate with ontologies in order to enhance the algorithm’s result. The experiments demonstrated a semantically improved result, generating more interesting clusters, therefore reducing manual analysis work of an expert.

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Objective The present study aimed to examine the reproducibility of heart rate (HR) and rating of perceived exertion (RPE) values obtained during different incremental treadmill tests. Equipment and methods Twenty male, recreational, endurance-trained runners (10-km running pace: 10–15 km·h−1) performed, in a counterbalanced order, three continuous incremental exercise tests with different speed increments (0.5 km·h−1, 1 km·h−1 and 2 km·h−1). Thereafter, each participant performed the three tests again, maintaining the same order as before. The reproducibility of the HR and RPE values were analyzed for all protocols during submaximal intensities (8, 10, 12, and 14 km·h−1). In addition, it was examined the reproducibility of maximal HR (HRmax) and peak RPE (RPEpeak). Results The variability of both the HR and RPE values showed a tendency to decrease over the stages during the incremental test and was not or slightly influenced by the incremental test design. The HR at 14 km·h−1 and HRmax presented the highest reproducibility (CV < 2%). In contrast, the submaximal RPE values showed higher variability indices (i.e., CV > 5.0%). In conclusion, the HR values were highly reproducible during the stages of the incremental test, in contrast to the RPE values that presented limited reproducibility.