Design of Intelligent Management Platform for Industry–Education Cooperation of Vocational Education by Data Mining

Data are playing an increasingly important role in the development of industry–education cooperation strategies in vocational education and training. The objective of this study was to promote the comprehensive progress of an industry–education cooperation system and improve the effect of the application of big data technology in this system. First, we designed of a big data technology application in an intelligent management platform system for industry–education cooperation. Second, we analyzed the synthetical design of the system. Finally, we optimized and designed a support vector machine (SVM) data mining (DM) algorithm model based on big data, and evaluated the model. The results revealed that the designed algorithm model provides outstanding advantages compared with similar algorithm models. In general, the highest average computation time of the designed SVM algorithm model is about 95 ms. The overall average calculation time linearly decreases around 200 iterations and tends to be stable, and the lowest overall average computation time is about 20 ms. In the DM process, the highest accuracy rate of the model is about 97%, and the lowest is about 92%. The DM accuracy rate is always stable as the number of iterations of the model continues to increase. The designed model slowly increases the occupancy rate of the system in the process of increasing computing time. At about 60 min, the system occupancy rate of the model tends to be stable, and the highest is maintained at about 23%. This study not only provides technical support for the optimization of DM algorithms with big data technology, but also contributes to the integrated development of industry–education cooperation systems.

Employment Management Policies for College Graduates under COVID-19 in China: Diffusion Characteristics and Core Issues.

The outbreak of COVID-19 epidemic has been having a great impact on the job market, so that graduates from all over the world are facing a more complex employment environment. Unemployment of the educated labor force often results in a waste of human capital and leads to serious economic and social problems. In the face of the impact of COVID-19, the Chinese government quickly introduced a series of employment policies for college graduates to relieve their employment pressure and create opportunities of career development. How did these employment policies for college graduates spread rapidly under the unconventional state of the COVID-19 epidemic? What are the diffusion characteristics? What are the core issues and measures? What are the differences between governments at all levels? These problems with rich connotation and research value needed to be further clarified. Based on the 72 employment support policies collected from the Chinese government network, this paper conducted a text analysis of the policies and found that in the process dimension, the employment policies of college graduates accumulated and exploded from bottom to top in the short term, and the policies diffusion followed the gradual model of "east-middle-west". In the content dimension, there were five core issues: financial subsidies, innovation and entrepreneurship to drive employment, public institutions to absorb, optimizing public services, and lowering the support threshold. Meanwhile, there were obvious differences in the choice of policy tools, policy intensity, and implementation ideas in each region. The findings are of important significance for developed and developing countries to better respond to the impact of various emergency situations.

Employment Management Policies for College Graduates under COVID-19 in China: Diffusion Characteristics and Core Issues

The outbreak of COVID-19 epidemic has been having a great impact on the job market, so that graduates from all over the world are facing a more complex employment environment. Unemployment of the educated labor force often results in a waste of human capital and leads to serious economic and social problems. In the face of the impact of COVID-19, the Chinese government quickly introduced a series of employment policies for college graduates to relieve their employment pressure and create opportunities of career development. How did these employment policies for college graduates spread rapidly under the unconventional state of the COVID-19 epidemic? What are the diffusion characteristics? What are the core issues and measures? What are the differences between governments at all levels? These problems with rich connotation and research value needed to be further clarified. Based on the 72 employment support policies collected from the Chinese government network, this paper conducted a text analysis of the policies and found that in the process dimension, the employment policies of college graduates accumulated and exploded from bottom to top in the short term, and the policies diffusion followed the gradual model of 'east–middle–west';. In the content dimension, there were five core issues: financial subsidies, innovation and entrepreneurship to drive employment, public institutions to absorb, optimizing public services, and lowering the support threshold. Meanwhile, there were obvious differences in the choice of policy tools, policy intensity, and implementation ideas in each region. The findings are of important significance for developed and developing countries to better respond to the impact of various emergency situations.

Author Correction: Temporal dynamics in viral shedding and transmissibility of COVID-19.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Temporal dynamics in viral shedding and transmissibility of COVID-19.

We report temporal patterns of viral shedding in 94 patients with laboratory-confirmed COVID-19 and modeled COVID-19 infectiousness profiles from a separate sample of 77 infector-infectee transmission pairs. We observed the highest viral load in throat swabs at the time of symptom onset, and inferred that infectiousness peaked on or before symptom onset. We estimated that 44% (95% confidence interval, 25-69%) of secondary cases were infected during the index cases' presymptomatic stage, in settings with substantial household clustering, active case finding and quarantine outside the home. Disease control measures should be adjusted to account for probable substantial presymptomatic transmission.

Real-time tentative assessment of the epidemiological characteristics of novel coronavirus infections in Wuhan, China, as at 22 January 2020.

A novel coronavirus (2019-nCoV) causing severe acute respiratory disease emerged recently in Wuhan, China. Information on reported cases strongly indicates human-to-human spread, and the most recent information is increasingly indicative of sustained human-to-human transmission. While the overall severity profile among cases may change as more mild cases are identified, we estimate a risk of fatality among hospitalised cases at 14% (95% confidence interval: 3.9-32%).