Aiming at the problems of the lack of sample size and the complexity of defect images in defect detection task, based on the idea of transfer learning and hierarchical feature fusion, this paper proposes a deep classification network model of improved vgg19 pre-training network by analyzing the basic principle of feature extraction of convolutional neural network and getting inspiration from feature pyramid network. Then, the model is trained by the small-scale defect images of solar pv panel. Finally, the solar pv panel data set containing four kinds of defects, including cracks, debris, broken gates and black areas, is selected to comprehensively verify the effectiveness of the improved network in the defect detection task. The experimental results show that the proposed method is superior to the classical vgg19 network model in four evaluation indexes, such as accuracy, precision, recall rate and F1 score.
The rice stem borer, Chilo suppressalis (Walker), and the rice leaf folder, Cnaphalocrocis medinalis Guenée, are two of the most destructive lepidopteran pests in rice. Since these two pyralid insects overlap in their occurrence in rice paddy fields, farmers prefer to set their pheromone-baited traps together in the rice fields for their monitoring. However, our field observation demonstrated that no male adult of C. suppressalis was captured in traps baited with commercial sex pheromone of C. suppressalis (CCS) combined with commercial sex pheromone of C. medinalis (CCM). To confirm that the C. medinalis sex pheromone component(s) interfere with the attraction of males of the rice stem borers to their conspecific females, single components of C. medinalis sex pheromone combined with CCS in traps were tested in the laboratory and rice paddy field. The results revealed that the two alcohol components in CCM, i.e., (Z)-11-octadecen-1-ol (Z11-18: OH) and (Z)-13-octadecen-1-ol (Z13-18: OH) may cause a significant reduction in capturing C. suppressalis males caused by CCS. We recommend against using these sex pheromones together in the field and suggest that Z11-18: OH and Z13-18: OH could be potential inhibitors or antagonists of C. suppressalis sex pheromone to control the rice stem borer.
The groundwater in Gaobeidian city is used for drinking, irrigation, industrial production, and other purposes. With the rapid development of the economy and urbanization, groundwater quality has been seriously affected. The main purposes of this paper are to evaluate the groundwater quality in the study area on the basis of understanding the hydrochemical characteristics of the study area and assess the possible health risks of groundwater to children and adults. In this paper, the entropy weight method was used to determine the weight of each evaluation parameter, and on this basis, groundwater quality evaluation was carried out, and the spatial distribution map of groundwater quality was drawn according to the evaluation results. The results show that the weight values of the five parameters of NO2–, Fe, As, Cr6+, and NO2–N are more than 0.1 among the total of fifteen parameters, and the concentration of these five parameters can be considered as the main influencing parameters of groundwater quality. The calculation results of the entropy weighted water quality index (EWQI) show that all the groundwater quality in the study area is class 1 water, which is Excellent Water. However, the EWQI value is the highest in the southwest of the study area, showing a trend of deterioration of groundwater water quality. Since all groundwater samples were evaluated as “excellent water,” it was speculated that the natural environment had more influence on groundwater chemical characteristics than human factors. The study found that 7.407% and 55.556% of the water samples posed a noncarcinogenic health risk to adults and children, respectively. The main responsible parameters for noncarcinogenic risk are F−, NO2−, NO3−, and Cr6+. The carcinogenic risk for adults ranged from 0 to 6.91E-04, with a mean of 1.00E-04. The carcinogenic risk for children ranged from 0 to 1.03E-03, with a mean of 1.55E-04. These toxic elements are mainly from industries. Therefore, the deterioration of groundwater quality can be prevented by strengthening the sewage management of various industries.
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