Soft measurement for component content based on adaptive model of Pr/Nd color features

For measurement of component content in the extraction and separation process of praseodymium/neodymium(Pr/Nd), a soft measurement method was proposed based on modeling of ion color features, which is suitable for fast estimation of component content in production field. Feature analysis on images of the solution is conducted,which are captured from Pr/Nd extraction/separation field. H/S components in the HSI color space are selected as model inputs, so as to establish the least squares support vector machine(LSSVM) model for Nd(Pr) content,while the model parameters are determined with the GA algorithm. To improve the adaptability of the model,the adaptive iteration algorithm is used to correct parameters of the LSSVM model, on the basis of model correction strategy and new sample data. Using the field data collected from rare earth extraction production, predictive methods for component content and comparisons are given. The results indicate that the proposed method presents good adaptability and high prediction precision, so it is applicable to the fast detection of element content in the rare earth extraction.

Analysis on the Content Features and Their Correlation of Web Pages for Spam Detection

In the global information era,people acquire more and more information from the Internet,but the quality of the search results is degraded strongly because of the presence of web spam.Web spam is one of the serious problems for search engines,and many methods have been proposed for spam detection.We exploit the content features of non-spam in contrast to those of spam.The content features for non-spam pages always possess lots of statistical regularities; but those for spam pages possess very few statistical regularities,because spam pages are made randomly in order to increase the page rank.In this paper,we summarize the regularities distributions of content features for non-spam pages,and propose the calculating probability formulae of the entropy and independent n-grams respectively.Furthermore,we put forward the calculation formulae of multi features correlation.Among them,the notable content features may be used as auxiliary information for spam detection.

QUANTITATIVE STUDIES ON THE DNA CONTENT AND MORPHOMETRIC FEATURES OF LIVER CELL DYSPLASIA

The DNA content and morphometric features of hepatocellular carcinoma (HCC) and liver cell dysplasia (LCD), including nuclear area, nuclear perimeter, nuclear maximum diameter and nuclear circle diameter, were quantitatively determined by means of image analysis technology. The results showed that in comparison with normal hepatocytes, LCD had a markedly increased DNA content and nuclear morphometric parameters, but the values were lower than those for HCC. LCD showed a slight increase in nuclear atypia represented by the nuclear irregular index, which was also less than HCC. The findings indicate that LCD may be a precaneerous lesion of HCC, to the cells in an abnormal proliferative state.