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Analyzing population of Streptococcus bacteria is important since these species can cause dental caries, periodontal, halitosis (bad breath) and more problems. This paper will discuss the phylogenetically relation between the bacterium Streptococcus in saliva using a phylogenetic tree of agglomerative clustering methods. Starting with the bacterium Streptococcus DNA sequence obtained from the GenBank, then performed characteristic extraction of DNA sequences. The characteristic extraction result is matrix form, then performed normalization using min-max normalization and calculate genetic distance using Manhattan distance. Agglomerative clustering technique consisting of single linkage, complete linkage and average linkage. In this agglomerative algorithm number of group is started with the number of individual species. The most similar species is grouped until the similarity decreases and then formed a single group. Results of grouping is a phylogenetic tree and branches that join an established level of distance, that the smaller the distance the more the similarity of the larger species implementation is using R, an open source program. [ABSTRACT FROM AUTHOR]

This paper studies the model of ultrasonic detection for composite material, and the characteristic extraction algorithm of echo signal based on wavelet transform. At first, we discussed characteristic and composing principle of the echo signal in detail, and based on this, a model is designed. It can be used to differentiate some classes' echo signal. And then, the wavelet transform was used to analyze echo signal, and some characteristics about energy and dimension were extracted in time-frequency domain. Simulation proves that the algorithm can recognize different echo signals effectively, and it is helpful to quantitative detection and recognition. [ABSTRACT FROM PUBLISHER]