Figure 1: Examples of the visual explanations in our experiment-We tested two ways to represent an example instance: (a) an image or (b) a rose chart of features, and three spatial layouts to arrange the instances: (c) grid, (d) tree, and (e) graph. Three images (c-e) here show explanations of the same instances, classifier, and classification recommendation.
A hydraulic turbine runner has a complex structure, and traditional source location methods do not have the higher accuracy to meet engineering requirements. The source location of crack acoustic emission (AE) signals in hydraulic turbine blades has been researched by combining it with kernel-independent component analysis (KICA) as feature extraction, with support vector machines (SVMs) as position recognition. This method is compared with those applied SVMs with feature extraction using kernel principal components analysis without feature extraction. The results show that the recognition rate in the crack region is 100 per cent by using both original AE parameters and feature parameters. Support vector regression by feature extraction using KICA can perform better than the other methods. As a result, it is a better method for source location of complex big size structures to combine KICA with SVM. It decreases the dimensionality of input signals and also improves the accuracy of location.
Mauremys sensu lato was divided into Mauremys, Chinemys, Ocadia, and Annamemys based on earlier research on morphology. Phylogenetic research on this group has been controversial because of disagreements regarding taxonomy, and the historical speciation is still poorly understood. In this study, 32 individuals of eight species that are widely distributed in Eurasia were collected. The complete mitochondrial (mt) sequences of 14 individuals of eight species were sequenced. Phylogenetic relationships, interspecific divergence times, and ancestral area reconstructions were explored using mt genome data (10,854 bp). Subsequent interspecific gene flow level assessment was performed using five unlinked polymorphic microsatellite loci. The Bayesian and maximum likelihood analyses revealed a paraphyletic relationship among four old genera (Mauremys, Annamemys, Chinemys, and Ocadia) and suggested the four old genera should be merged into the genus (Mauremys). Ancestral area reconstruction and divergence time estimation suggested Southeast Asia may be the area of origin for the common ancestral species of this genus and genetic drift may have played a decisive role in species divergence due to the isolated event of a glacial age. However, M. japonica may have been speciated due to the creation of the island of Japan. The detection of extensive gene flow suggested no vicariance occurred between Asia and Southeast Asia. Inconsistent results between gene flow assessment and phylogenetic analysis revealed the hybrid origin of M. mutica (Southeast Asian). Here ancestral area reconstruction and interspecific gene flow level assessment were first used to explore species origins and evolution of Mauremys sensu lato, which provided new insights on this genus.
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