The research aims at identifying the patterns in the use of the metaphor of illness as a tool of media rhetoric in the Chinese mass media texts (both in Chinese and in English). Chinese periodicals published in different languages are not translations from Chinese. The metaphor of illness, realised through the words and phrases on medical topics, is a means of introducing social and international issues in the Chinese mass media in English and Chinese. The metaphor is studied as a rhetoric tool that increases the pragmatic efficiency of the media material. The metaphor of illness functions as one of the strongest ways of affecting the emotion and volition sphere of the addressee and exercising control over mass consciousness. The research is novel in that it identifies the national-cultural specificity of the use of the metaphor of illness in the Chinese media text (both in English and in Chinese). As a result, metaphorical models have been identified in the mass media presentation of international and social problems as health-related issues (physical and mental health). The projection of a holistic health approach on public problems is reflected in the proposed models for solving complex social and international issues. The way out of the problematic situation is seen in changing the lifestyle of the society itself, in focusing on the internal forces of the society as a single organism, rather than relying on external help.
Deep convolutional neural networks in hyperspectral remote sensing data processing During the last decade the deep convolutional neural networks (DСNN) were successfully applied in the fields related to processing of large satellite images of high resolution that are used in various inverse problems on retrieval of the earth atmosphere characteristics and the earth boundary reflectance via remote sensing data analysis. The presented paper contains the information on the research state related to application of neural network methods to satellite hyper-spectral image processing, including brief information on the main features of convolutional neural networks (CNN), deep learning (DL) and autoencoders (AE) that are used for information compression. Up to present time a considerable number of DСNN models created is located for open access in the Internet. These verified models with well performance allow to develop new advanced models of DСNN. A brief information on some Internet models of open access is contained in the present paper. A more detailed information on neural network models located in open Internet access, and also on large data sets that are necessary for DСNN tuning, will be contained in the second part of the present paper, that is planned to be published.
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