Background : China is a country with a high burden of pulmonary tuberculosis (PTB), and the number of patient ranks second place in the world. Chongqing is the only municipality in the southwest of China directly under the Central Government, where the notification rate of PTB ranks top ten in China. This study analyzed the temporal and spatial distribution characteristics of PTB in Chongqing in order to take more powerful control measures. Methods : A spatial-temporal analysis has been performed based on the data of PTB from 2011 to 2018, which was extracted from the National Surveillance System. Time series, spatial autonomic correlation and spatial-temporal scanning methods were used to identify the temporal trends and spatial patterns at county level. Results : A total of 188,528 cases were included in this study. A downward trend was observed in the epidemic of PTB in Chongqing from 2011 to 2018. The peak of PTB notification was present in late winter and early spring season each year. By calculating the value of Global Moran's I and Local Getis’s Gi*, we found that PTB was spatially clustered and some significant hot spots were detected in the southeast and northeast of Chongqing. One most likely cluster and three secondary clusters were identified by Kulldorff’s scan spatial-temporal Statistic. Conclusions : This study identified seasonal patterns and spatial-temporal clusters of PTB cases in Chongqing. The results provide us useful information for developing subsequent TB control measures.
Smart medical care will realize the self-management, selection, and optimization of related things with more thorough induction, more comprehensive interconnection, and more intelligent insight, so that people can get an increasingly personalized medical and health service experience. 5G-enabled Internet of Things and AI (artificial intelligence) will continue to drive innovative applications in the medical industry. Access control and sharing of medical data is of great significance to the development of smart medical care, but the security problems in medical data sharing cannot be ignored. In this paper, a privacy protection scheme of medical service data based on blockchain and AI is proposed. The user chain is constructed as a public chain. In the user chain, the data privacy of users is protected, and users can safely transmit data to doctors and realize the management of session keys. CNN (convolutional neural network) privacy protection protocol based on homomorphic encryption can protect users’ privacy input, server model parameters, and calculated intermediate values. Experimental analysis and comparison with other schemes show that the scheme in this model is safer and more practical.
The current status of the industrial production process was introduced in this paper firstly, and then, this paper introduced the purpose and meaning of designing the intelligent computing platform, it makes detailed description about the architecture and design schema, and specifies function of modules respectively. It introduces the related technology of J2EE and .net standard framework, discusses how to put up the basic architecture of industrial intelligent computing platform, which could provide an intelligent computing platform with high reliability, ease expansibility, reusability and security. On this basis, the overall design and related technology of the platform is mainly discussed, furthermore, it also gives a simple implementation of the platform. With the platform, the guiding function of the history industrial data to the production process will be improved. It realizes the data value increment, and it is beneficial to realize the goal of the "informatization driving industrialization".
This chapter presents an analysis of long-term trends of air temperature, precipitation, aridity, the interdecadal features and spatial variation of the main pastoral regions of China based on statistical data on annual temperature and precipitation from 173 meteorological stations from 1951 to 2004. It is established that over the past years, there is a distinct warming trend, with a definite shift to warmer temperatures in the late 1980s. The coldest period was in the 1960s, the warmest period in the middle/late 1990s and the warmest year was 1998. Annual precipitation varies significantly, with a general rising trend but with a relative shortage period of rain/snow in the 1960s/1970s and relatively ample rain/snow in the 1990s and early 21st century. The highest precipitation year was 2003. Finally, the impact of these climatic changes on people, livestock and plants is also analysed.
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