Behavior identification based on geotagged photo data set.

The popularity of mobile devices has produced a set of image data with geographic information, time information, and text description information, which is called geotagged photo data set. The division of this kind of data by its behavior and the location not only can identify the user's important location and daily behavior, but also helps users to sort the huge image data. This paper proposes a method to build an index based on multiple classification result, which can divide the data set multiple times and distribute labels to the data to build index according to the estimated probability of classification results in order to accomplish the identification of users' important location and daily behaviors. This paper collects 1400 discrete sets of data as experimental data to verify the method proposed in this paper. The result of the experiment shows that the index and actual tagging results have a high inosculation.

Study on quality assessment of Polygalae Radix based on HPLC-DAD fingerprint / 中国中药杂志

<p><b>OBJECTIVE</b>To establish an HPLC fingerprint to evaluate the quality of Polygalae Radix, root xylem, and those collected in different growth ages or harvest time.</p><p><b>METHOD</b>Separation was performed at 30 °C on a Kromasil C18 column (4.6 mm x 250 mm, 5 μm); the mobile phases was acetonitrile and 0.05% H3PO4 water in the gradient elution; the flow rate was set at 1.0 mL · min(-1) and the detection wavelength at 314 nm; the quality discriminant analyses were accomplished by means of similarity analysis, cluster analysis, principal component analysis and neural network model.</p><p><b>RESULT</b>In 26 batches of Polygalae Radix, 24 batches fingerprint similarities were above 0.8. In 5 different growth or harvest time batches, 4 batches were above 0.8; in 8 batches root xylem samples, the similarities were all above 0.875. The similarity analysis was in accord with the quality discriminant analysis of cluster analysis, principal component analysis and neural network model.</p><p><b>CONCLUSION</b>Fingerprint combined with chemical pattern recognition technique can effectively evaluate the quality of Polygalae Radix. The active substance species are all similar in cultivated, wild, different growth or harvest time Polygalae Radix and polygala root xylem, but the chromatography peak areas are different. The effective material contents are similar between wild and cultivated Polygalae Radix, but each chromatographic peak area of the root xylem is much smaller than that of Polygalae Radix. The chemical substance accumulation mainly depends on harvest month, but little growth time in Polygalae Radix.</p>