A new method to generate radar air intelligent information by using data mining techniques based on historical radar data is proposed. This method has two stages: One is “filtering separation - piecewise fitting - feature clustering". In this stage, the radar historical data is divided into the actual true track and noise. Through computing the second-order discrete curvature, the actual true track is decomposed into several segments, such as straight line and arc, which are fitted with multinomial subsequently. On this basis, after analyzing the characteristic vector of radar historical data, the clustering database is established; the other is “feature association-track recombination”. The track in pre-deigned air scenario is segmented by the second-order discrete curvature. After the correlative feature information of the segmented scenario is searched, matched and associated with the information in clustering database, a new track will be restructured by using this output results. This method is very available for its effective application in simulation test-bed of C3I system.

In order to improve the rearing of Coccinella septempunctata L. (Coleoptera: Coccinellidae), nutrients such as shrimp, pollen, honey, and lard were added to the basic artificial diet, and the effects of the artificial diet on biological parameters and digestive enzymes were evaluated. The results show that beetles feeding on the supplemented diet exhibited pupation, emergence, fecundity, and hatching rates that were 102.69%, 125.02%, 162.33%, and 119.90% of those supplied with the basic diet, respectively. The addition of shrimp and pollen to the basal diet improved protease, trypsin, chymotrypsin, and aminopeptidase activity in larvae and female adults. The addition of lard improved lipase activity in female adults, and the addition of honey improved invertase activity in adults of both sexes. This study provides guidance for improving the nutritional benefits of ladybug artificial diets.

No abstract

No abstract