Financial Management Early-Warning Mechanism Construction and Decision Analysis Research Based on Wireless Sensor Network and Data Mining

With the gradual and complete establishment of the current socialist legal market economy management system with Chinese characteristics and the continuous investment in deepening system reform and continuous improvement in the later period, the social financial industry and corporate financial management have gradually increased their risk awareness of corporate financial management. This paper deeply analyzes and studies the statistical methods of financial data-related legal rule interactive mining and proposes a new improved statistical algorithm of financial-related legal rules, which greatly improves the work efficiency of financial data interactive mining. At the same time, a multilevel analysis model based on the concept of corporate financial crisis risk assessment and a corporate financial crisis risk early-warning analysis model for decision-making risk evaluation are proposed. Finally, it can be determined how to choose more internationally representative corporate financial management risk analysis indicators, which have more objectivity and practical application significance than traditional analysis methods. Finally, it is concluded that the accuracy of this model is better than that of other models. The accuracy rate of financial crisis prediction reached 62.35%.

Intelligent Strategies to Improve Food Safety Supervision Model

Intelligent supervision effectively deals with food safety problems from four aspects: concept, subject, activity and object. This paper makes a qualitative analysis on the current situation of intelligent supervision of food safety in Beijing, Tianjin and Hebei, compares and studies the intelligent supervision modes of food safety in three coastal areas in eastern China, constructs the analysis framework of intelligent supervision of food safety, and improves the intelligent supervision mode of food safety in Beijing, Tianjin and Hebei. By studying the policy path of intelligent supervision of food safety, extract the three-stage three source stream model of supervision mode from standard cultivation, informatization to standard unification and intelligence, to better promote the intelligent supervision mode in the country. For the challenges still faced by food safety supervision, it is proposed to improve the top-level design and strengthen the intelligent supervision mechanism of cross regional coordination; Promote the cooperation and sharing of data resources and optimize the cross regional risk early warning mechanism; Consolidate the rural digital foundation and realize the integration mechanism of urban and rural food safety supervision.

Outside Dynamic Evacuation Routes to Escape a Wildfire: A Prototype App for Forest Firefighters

This paper describes a prototype application to use different algorithms for creating optimal evacuation routes in the presence of a wildfire with a dynamic event-based update. The application uses a meteorological API that obtains real-time temperature, atmospheric pressure, humidity, speed, and wind direction of each location within an area using geographic coordinates (latitude and longitude) for creating a sensor network. The data are stored in a database for monitoring and visualization using the open-source platform Grafana, which includes an early warning mechanism that sends messages when it detects a temperature outside the normal range. Three different simulation scenarios were evaluated, varying the fire’s starting point coordinates and the evacuation route. The results show that the algorithm reacts to the presence of fire, maximizing safety margins even on longer evacuation routes. The prototype can be used to create an application to fight forest fires and safeguard rescue agents’ lives.

Investigating the correlation of COVID-19 spread with Baidu search data : Infoveillance Study (Preprint)

BACKGROUND The sudden outbreak of COVID-19 has placed an unprecedented pressure on China's public health system. It is imperative to strengthen the capacity of early surveillance and early warning to build a sound public health system. Therefore, it is necessary to improve the multi-channel monitoring and early warning mechanism to improve the ability of real-time analysis and judgment. OBJECTIVE To explore the correlation of COVID-19 spread with Baidu search data in Beijing, so as to evaluate the possibility of monitoring the epidemic situation of COVID-19 with Baidu search data. METHODS This study compared the daily case counts of COVID-19 outbreak from January 20 to March 1, 2020 with Baidu search data for the same period in Beijing. After keyword selection, filtering and composition, the most correlated lag of the COVID-19 Baidu Search Index (CBSI) was used for comparison and linear regression model development. RESULTS Our findings showed a positive relationship of CBSI and the confirmed cases of COVID-19 (ρ=0.711, P < .001). The strongest correlation between COVID-19 confirmed cases and indices, CBSI, was at a lag of -11 days. The regression coefficient β1 of the established regression model was equal to 1.042 (P<.001), R2 was equal to 0.7, which indicated that Baidu search data could reflect 70% of the variation in COVID-19 cases. CONCLUSIONS COVID-19 Baidu Search index may be a good monitoring indicator for early detection of COVID-19 outbreaks.